data
dict |
|---|
{
"proceeding": {
"id": "1cJ6WsGCn96",
"title": "2018 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"acronym": "vast",
"groupId": "1001630",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "1cJ6YwLGq40",
"doi": "10.1109/VAST.2018.8802486",
"title": "SMARTexplore: Simplifying High-Dimensional Data Analysis through a Table-Based Visual Analytics Approach",
"normalizedTitle": "SMARTexplore: Simplifying High-Dimensional Data Analysis through a Table-Based Visual Analytics Approach",
"abstract": "We present SMARTEXPLORE, a novel visual analytics technique that simplifies the identification and understanding of clusters, correlations, and complex patterns in high-dimensional data. The analysis is integrated into an interactive table-based visualization that maintains a consistent and familiar representation throughout the analysis. The visualization is tightly coupled with pattern matching, subspace analysis, reordering, and layout algorithms. To increase the analyst's trust in the revealed patterns, SMARTEXPLORE automatically selects and computes statistical measures based on dimension and data properties. While existing approaches to analyzing high-dimensional data (e.g., planar projections and Parallel coordinates) have proven effective, they typically have steep learning curves for non-visualization experts. Our evaluation, based on three expert case studies, confirms that non-visualization experts successfully reveal patterns in high-dimensional data when using SMARTEXPLORE.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present SMARTEXPLORE, a novel visual analytics technique that simplifies the identification and understanding of clusters, correlations, and complex patterns in high-dimensional data. The analysis is integrated into an interactive table-based visualization that maintains a consistent and familiar representation throughout the analysis. The visualization is tightly coupled with pattern matching, subspace analysis, reordering, and layout algorithms. To increase the analyst's trust in the revealed patterns, SMARTEXPLORE automatically selects and computes statistical measures based on dimension and data properties. While existing approaches to analyzing high-dimensional data (e.g., planar projections and Parallel coordinates) have proven effective, they typically have steep learning curves for non-visualization experts. Our evaluation, based on three expert case studies, confirms that non-visualization experts successfully reveal patterns in high-dimensional data when using SMARTEXPLORE.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present SMARTEXPLORE, a novel visual analytics technique that simplifies the identification and understanding of clusters, correlations, and complex patterns in high-dimensional data. The analysis is integrated into an interactive table-based visualization that maintains a consistent and familiar representation throughout the analysis. The visualization is tightly coupled with pattern matching, subspace analysis, reordering, and layout algorithms. To increase the analyst's trust in the revealed patterns, SMARTEXPLORE automatically selects and computes statistical measures based on dimension and data properties. While existing approaches to analyzing high-dimensional data (e.g., planar projections and Parallel coordinates) have proven effective, they typically have steep learning curves for non-visualization experts. Our evaluation, based on three expert case studies, confirms that non-visualization experts successfully reveal patterns in high-dimensional data when using SMARTEXPLORE.",
"fno": "08802486",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Interactive Systems",
"Pattern Clustering",
"Statistical Analysis",
"SMAR Texplore",
"High Dimensional Data Analysis",
"Interactive Table Based Visualization",
"Pattern Matching",
"Subspace Analysis",
"Table Based Visual Analytics",
"Reordering",
"Layout Algorithms",
"Statistical Measures",
"Tabular Visualization",
"Data Visualization",
"Correlation",
"Tools",
"Reliability",
"Visual Analytics",
"Task Analysis",
"High Dimensional Data",
"Visual Exploration",
"Pattern Driven Analysis",
"Tabular Visualization",
"Subspace",
"Aggregation"
],
"authors": [
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Michael Blumenschein",
"givenName": "Michael",
"surname": "Blumenschein",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Harvard University, USA",
"fullName": "Michael Behrisch",
"givenName": "Michael",
"surname": "Behrisch",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Stefanie Schmid",
"givenName": "Stefanie",
"surname": "Schmid",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Simon Butscher",
"givenName": "Simon",
"surname": "Butscher",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Deborah R. Wahl",
"givenName": "Deborah R.",
"surname": "Wahl",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Karoline Villinger",
"givenName": "Karoline",
"surname": "Villinger",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Britta Renner",
"givenName": "Britta",
"surname": "Renner",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Harald Reiterer",
"givenName": "Harald",
"surname": "Reiterer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Konstanz, Germany",
"fullName": "Daniel A. Keim",
"givenName": "Daniel A.",
"surname": "Keim",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vast",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-10-01T00:00:00",
"pubType": "proceedings",
"pages": "36-47",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-6861-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08802383",
"articleId": "1cJ6Yd3Hh6g",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08802454",
"articleId": "1cJ6YEzEuQ0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/pacificvis/2018/1424/0/142401a160",
"title": "Visual Analytics for Networked-Guarantee Loans Risk Management",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2018/142401a160/12OmNBpVPS1",
"parentPublication": {
"id": "proceedings/pacificvis/2018/1424/0",
"title": "2018 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/10/07346501",
"title": "PeakVizor: Visual Analytics of Peaks in Video Clickstreams from Massive Open Online Courses",
"doi": null,
"abstractUrl": "/journal/tg/2016/10/07346501/13rRUILtJme",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07534792",
"title": "A Visual Analytics Approach for Categorical Joint Distribution Reconstruction from Marginal Projections",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07534792/13rRUxDIthg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013121982",
"title": "Vis4Heritage: Visual Analytics Approach on Grotto Wall Painting Degradations",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013121982/13rRUy2YLT1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440040",
"title": "A Visual Analytics Framework for Spatiotemporal Trade Network Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440040/17D45WHONjL",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2019/9226/0/922600a237",
"title": "Designing Narrative Slideshows for Learning Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2019/922600a237/1cMF6FsJ8zK",
"parentPublication": {
"id": "proceedings/pacificvis/2019/9226/0",
"title": "2019 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/04/08984335",
"title": "PeckVis: A Visual Analytics Tool to Analyze Dominance Hierarchies in Small Groups",
"doi": null,
"abstractUrl": "/journal/tg/2020/04/08984335/1haTxOaV8eA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222086",
"title": "<italic>PipelineProfiler:</italic> A Visual Analytics Tool for the Exploration of AutoML Pipelines",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222086/1nTrpup4LZe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a336",
"title": "VaBank: Visual Analytics for Banking Transactions",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a336/1rSRewueIso",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/2021/4121/0/412100a125",
"title": "I-CovidVis – A Visual Analytics Tool for Interoperable Healthcare Databases using Graphs",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2021/412100a125/1vb8Nrw0m7m",
"parentPublication": {
"id": "proceedings/cbms/2021/4121/0",
"title": "2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1nMQuhwnpRu",
"title": "2020 IEEE 28th International Requirements Engineering Conference (RE)",
"acronym": "re",
"groupId": "1000630",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1nMQvWQVXBC",
"doi": "10.1109/RE48521.2020.00022",
"title": "How developers believe Invisibility impacts NFRs related to User Interaction",
"normalizedTitle": "How developers believe Invisibility impacts NFRs related to User Interaction",
"abstract": "The advance of Ubiquitous Computing (UbiComp) and Internet of Things (IoT) brought a new set of Non-Functional Requirements (NFRs), especially related to Human-Computer Interaction (HCI). Invisibility is one of these NFRs, and it refers to either the merging of technology in the user environment or the decrease of the interaction workload. This new NFR may impact traditional NFRs (e.g., Usability), revealing positive correlations, when one NFR helps another, and negative correlations, when a procedure favors an NFR but creates difficulty for another one. Software engineers need to know about these correlations, so they can select appropriate strategies to satisfy Invisibility and traditional NFRs. Correlations between NFRs are usually stored in catalogs, which is a well-defined body of knowledge gathered from previous experience. Although Invisibility has been recently cataloged with development strategies, the literature still lacks catalogs with correlations for this NFR. Therefore, this work aims at capturing and cataloging invisibility correlations for UbiComp and IoT systems. To do that, we also propose to systematize the definition of correlations using the following well-defined research methods: Interview, Content Analysis and Questionnaire. As a result, we defined a catalog with 110 positive and negative correlations with 9 NFRs. This well-defined body of knowledge is useful for supporting software engineers to select strategies to satisfy Invisibility and other NFRs related to user interaction.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The advance of Ubiquitous Computing (UbiComp) and Internet of Things (IoT) brought a new set of Non-Functional Requirements (NFRs), especially related to Human-Computer Interaction (HCI). Invisibility is one of these NFRs, and it refers to either the merging of technology in the user environment or the decrease of the interaction workload. This new NFR may impact traditional NFRs (e.g., Usability), revealing positive correlations, when one NFR helps another, and negative correlations, when a procedure favors an NFR but creates difficulty for another one. Software engineers need to know about these correlations, so they can select appropriate strategies to satisfy Invisibility and traditional NFRs. Correlations between NFRs are usually stored in catalogs, which is a well-defined body of knowledge gathered from previous experience. Although Invisibility has been recently cataloged with development strategies, the literature still lacks catalogs with correlations for this NFR. Therefore, this work aims at capturing and cataloging invisibility correlations for UbiComp and IoT systems. To do that, we also propose to systematize the definition of correlations using the following well-defined research methods: Interview, Content Analysis and Questionnaire. As a result, we defined a catalog with 110 positive and negative correlations with 9 NFRs. This well-defined body of knowledge is useful for supporting software engineers to select strategies to satisfy Invisibility and other NFRs related to user interaction.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The advance of Ubiquitous Computing (UbiComp) and Internet of Things (IoT) brought a new set of Non-Functional Requirements (NFRs), especially related to Human-Computer Interaction (HCI). Invisibility is one of these NFRs, and it refers to either the merging of technology in the user environment or the decrease of the interaction workload. This new NFR may impact traditional NFRs (e.g., Usability), revealing positive correlations, when one NFR helps another, and negative correlations, when a procedure favors an NFR but creates difficulty for another one. Software engineers need to know about these correlations, so they can select appropriate strategies to satisfy Invisibility and traditional NFRs. Correlations between NFRs are usually stored in catalogs, which is a well-defined body of knowledge gathered from previous experience. Although Invisibility has been recently cataloged with development strategies, the literature still lacks catalogs with correlations for this NFR. Therefore, this work aims at capturing and cataloging invisibility correlations for UbiComp and IoT systems. To do that, we also propose to systematize the definition of correlations using the following well-defined research methods: Interview, Content Analysis and Questionnaire. As a result, we defined a catalog with 110 positive and negative correlations with 9 NFRs. This well-defined body of knowledge is useful for supporting software engineers to select strategies to satisfy Invisibility and other NFRs related to user interaction.",
"fno": "09218217",
"keywords": [
"Formal Specification",
"Human Computer Interaction",
"Internet Of Things",
"Software Engineering",
"User Interaction",
"Ubiquitous Computing",
"Ubi Comp",
"Nonfunctional Requirements",
"Human Computer Interaction",
"User Environment",
"Interaction Workload",
"Invisibility Correlations",
"Internet Of Things",
"HCI",
"Io T Systems",
"Content Analysis",
"Correlation",
"Pervasive Computing",
"Usability",
"Interviews",
"Security",
"Internet Of Things",
"Human Computer Interaction",
"Invisibility",
"Correlation",
"Cooperation",
"Conflict",
"Non Functional Requirement",
"Catalog"
],
"authors": [
{
"affiliation": "Federal University of Ceará,Computer Science Department (DC),Fortaleza,Brazil",
"fullName": "Rainara Maia Carvalho",
"givenName": "Rainara Maia",
"surname": "Carvalho",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Federal University of Ceará,Computer Science Department (DC),Fortaleza,Brazil",
"fullName": "Rossana M. C. Andrade",
"givenName": "Rossana M. C.",
"surname": "Andrade",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Université Polytechnique Hauts-de-France, Valenciennes, LAMIH UMR CNRS 8201,Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science,France",
"fullName": "Káthia M. Oliveira",
"givenName": "Káthia M.",
"surname": "Oliveira",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "re",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-08-01T00:00:00",
"pubType": "proceedings",
"pages": "102-112",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-7438-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09218160",
"articleId": "1nMQuHZC5Ww",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09218138",
"articleId": "1nMQxFHcQ7e",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/re/2017/3191/0/3191a544",
"title": "Dealing with Conflicts Between Non-functional Requirements of UbiComp and IoT Applications",
"doi": null,
"abstractUrl": "/proceedings-article/re/2017/3191a544/12OmNClQ0ql",
"parentPublication": {
"id": "proceedings/re/2017/3191/0",
"title": "2017 IEEE 25th International Requirements Engineering Conference (RE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/msr/2015/5594/0/5594a446",
"title": "Which Non-functional Requirements Do Developers Focus On? An Empirical Study on Stack Overflow Using Topic Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/msr/2015/5594a446/12OmNzahca7",
"parentPublication": {
"id": "proceedings/msr/2015/5594/0",
"title": "2015 IEEE/ACM 12th Working Conference on Mining Software Repositories (MSR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/re/2018/7418/0/741800a088",
"title": "Catalog of Invisibility Requirements for UbiComp and IoT Applications",
"doi": null,
"abstractUrl": "/proceedings-article/re/2018/741800a088/17D45WHONpc",
"parentPublication": {
"id": "proceedings/re/2018/7418/0",
"title": "2018 IEEE 26th International Requirements Engineering Conference (RE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1rqEvqZWX6w",
"title": "2020 IEEE/ACM Symposium on Edge Computing (SEC)",
"acronym": "sec",
"groupId": "1816984",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1rqEwMGd8zK",
"doi": "10.1109/SEC50012.2020.00016",
"title": "Spatula: Efficient cross-camera video analytics on large camera networks",
"normalizedTitle": "Spatula: Efficient cross-camera video analytics on large camera networks",
"abstract": "Cameras are deployed at scale with the purpose of searching and tracking objects of interest (e.g., a suspected person) through the camera network on live videos. Such cross-camera analytics is data and compute intensive, whose costs grow with the number of cameras and time. We present Spatula, a cost-efficient system that enables scaling cross-camera analytics on edge compute boxes to large camera networks by leveraging the spatial and temporal cross-camera correlations. While such correlations have been used in computer vision community, Spatula uses them to drastically reduce the communication and computation costs by pruning search space of a query identity (e.g., ignoring frames not correlated with the query identity's current position). Spatula provides the first system substrate on which cross-camera analytics applications can be built to efficiently harness the cross-camera correlations that are abundant in large camera deployments. Spatula reduces compute load by 8.3× on an 8-camera dataset, and by 23 × -86× on two datasets with hundreds of cameras (simulated from real vehicle/pedestrian traces). We have also implemented Spatula on a testbed of 5 AWS DeepLens cameras.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cameras are deployed at scale with the purpose of searching and tracking objects of interest (e.g., a suspected person) through the camera network on live videos. Such cross-camera analytics is data and compute intensive, whose costs grow with the number of cameras and time. We present Spatula, a cost-efficient system that enables scaling cross-camera analytics on edge compute boxes to large camera networks by leveraging the spatial and temporal cross-camera correlations. While such correlations have been used in computer vision community, Spatula uses them to drastically reduce the communication and computation costs by pruning search space of a query identity (e.g., ignoring frames not correlated with the query identity's current position). Spatula provides the first system substrate on which cross-camera analytics applications can be built to efficiently harness the cross-camera correlations that are abundant in large camera deployments. Spatula reduces compute load by 8.3× on an 8-camera dataset, and by 23 × -86× on two datasets with hundreds of cameras (simulated from real vehicle/pedestrian traces). We have also implemented Spatula on a testbed of 5 AWS DeepLens cameras.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cameras are deployed at scale with the purpose of searching and tracking objects of interest (e.g., a suspected person) through the camera network on live videos. Such cross-camera analytics is data and compute intensive, whose costs grow with the number of cameras and time. We present Spatula, a cost-efficient system that enables scaling cross-camera analytics on edge compute boxes to large camera networks by leveraging the spatial and temporal cross-camera correlations. While such correlations have been used in computer vision community, Spatula uses them to drastically reduce the communication and computation costs by pruning search space of a query identity (e.g., ignoring frames not correlated with the query identity's current position). Spatula provides the first system substrate on which cross-camera analytics applications can be built to efficiently harness the cross-camera correlations that are abundant in large camera deployments. Spatula reduces compute load by 8.3× on an 8-camera dataset, and by 23 × -86× on two datasets with hundreds of cameras (simulated from real vehicle/pedestrian traces). We have also implemented Spatula on a testbed of 5 AWS DeepLens cameras.",
"fno": "594300a110",
"keywords": [
"Cameras",
"Computational Complexity",
"Computer Vision",
"Object Detection",
"Object Tracking",
"Video Signal Processing",
"Video Surveillance",
"Spatula",
"Cross Camera Video Analytics",
"Camera Network",
"Cost Efficient System",
"Edge Compute Boxes",
"Spatial Cross Camera Correlations",
"Temporal Cross Camera Correlations",
"Computer Vision Community",
"Computation Costs",
"Cross Camera Analytics Applications",
"Camera Deployments",
"5 AWS Deep Lens Cameras",
"Correlation",
"Visual Analytics",
"Cameras",
"Search Problems",
"Substrates",
"Videos",
"Edge Computing",
"Video Analytics",
"Edge Computing",
"Cross Camera Analytics",
"Spatial Temporal Correlations"
],
"authors": [
{
"affiliation": "UC Berkeley",
"fullName": "Samvit Jain",
"givenName": "Samvit",
"surname": "Jain",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chicago",
"fullName": "Xun Zhang",
"givenName": "Xun",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chicago",
"fullName": "Yuhao Zhou",
"givenName": "Yuhao",
"surname": "Zhou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Microsoft Research",
"fullName": "Ganesh Ananthanarayanan",
"givenName": "Ganesh",
"surname": "Ananthanarayanan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chicago",
"fullName": "Junchen Jiang",
"givenName": "Junchen",
"surname": "Jiang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Microsoft Research",
"fullName": "Yuanchao Shu",
"givenName": "Yuanchao",
"surname": "Shu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Microsoft Research",
"fullName": "Paramvir Bahl",
"givenName": "Paramvir",
"surname": "Bahl",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "UC Berkeley",
"fullName": "Joseph Gonzalez",
"givenName": "Joseph",
"surname": "Gonzalez",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "sec",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-11-01T00:00:00",
"pubType": "proceedings",
"pages": "110-124",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-5943-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "594300a096",
"articleId": "1rqEx8lYcla",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "594300a125",
"articleId": "1rqEzRatpw4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/hpcc-dss-smartcity-dependsys/2021/9457/0/945700a699",
"title": "Research on Cross-Camera Person Re-Identification Using Overlapping Field of View",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-dss-smartcity-dependsys/2021/945700a699/1DNCAisD7Yk",
"parentPublication": {
"id": "proceedings/hpcc-dss-smartcity-dependsys/2021/9457/0",
"title": "2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcc-dss-smartcity-dependsys/2021/9457/0/945700b397",
"title": "On-Camera Content Filtering for Real-Time Video Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-dss-smartcity-dependsys/2021/945700b397/1DNE1uTGHIc",
"parentPublication": {
"id": "proceedings/hpcc-dss-smartcity-dependsys/2021/9457/0",
"title": "2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859614",
"title": "Maxim: DRL-Based Cross-Camera Streaming Configuration for Real-Time Video Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859614/1G9Etvks7Wo",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdcs/2022/7177/0/717700a503",
"title": "Multi-View Scheduling of Onboard Live Video Analytics to Minimize Frame Processing Latency",
"doi": null,
"abstractUrl": "/proceedings-article/icdcs/2022/717700a503/1HriMIaxdfi",
"parentPublication": {
"id": "proceedings/icdcs/2022/7177/0",
"title": "2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mass/2022/7180/0/718000a394",
"title": "Adaptive Cross-Camera Video Analytics at the Edge",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2022/718000a394/1JeEkn9IIVO",
"parentPublication": {
"id": "proceedings/mass/2022/7180/0",
"title": "2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/percom/2023/5378/0/10099298",
"title": "PreActo: Efficient Cross-Camera Object Tracking System in Video Analytics Edge Computing",
"doi": null,
"abstractUrl": "/proceedings-article/percom/2023/10099298/1MrG8HKt6GA",
"parentPublication": {
"id": "proceedings/percom/2023/5378/0",
"title": "2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ic/2019/04/08874984",
"title": "Live Video Analytics",
"doi": null,
"abstractUrl": "/magazine/ic/2019/04/08874984/1ecAKNkUNTa",
"parentPublication": {
"id": "mags/ic",
"title": "IEEE Internet Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2020/06/08976261",
"title": "A Fast Filtering Mechanism to Improve Efficiency of Large-Scale Video Analytics",
"doi": null,
"abstractUrl": "/journal/tc/2020/06/08976261/1h0W7enz1aU",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/percom-workshops/2020/4716/0/09156251",
"title": "CONVINCE: Collaborative Cross-Camera Video Analytics at the Edge",
"doi": null,
"abstractUrl": "/proceedings-article/percom-workshops/2020/09156251/1m1jCustMFW",
"parentPublication": {
"id": "proceedings/percom-workshops/2020/4716/0",
"title": "2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/nt/2022/02/09622882",
"title": "Scheduling Massive Camera Streams to Optimize Large-Scale Live Video Analytics",
"doi": null,
"abstractUrl": "/journal/nt/2022/02/09622882/1yJSYPPtBPG",
"parentPublication": {
"id": "trans/nt",
"title": "IEEE/ACM Transactions on Networking",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yylaxRHvDW",
"title": "2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)",
"acronym": "acii",
"groupId": "1002992",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yyleElWpS8",
"doi": "10.1109/ACII52823.2021.9597457",
"title": "Trace It Like You Believe It: Time-Continuous Believability Prediction",
"normalizedTitle": "Trace It Like You Believe It: Time-Continuous Believability Prediction",
"abstract": "Assessing the believability of agents, characters and simulated actors is a core challenge for human computer interaction. While numerous approaches are suggested in the literature, they are all limited to discrete and low-granularity representations of believable behavior. In this paper we view believability, for the first time, as a time-continuous phenomenon and we explore the suitability of two different affect annotation schemes for its assessment. In particular, we study the degree to which we can predict character believability in a continuous fashion through a two-player game study. The game features various opponent behaviors that are assessed for their believability by 89 participants that played the game and then annotated their recorded playthrough. Random forest models are then trained to predict believability based on ad-hoc designed in-game features. Results suggest that a discrete annotation method leads to a more robust assessment of the ground truth and subsequently better modelling performance. Our best models are able to predict a change in perceived believability with a 72.5% accuracy on average (up to 90% in the best cases) in a time-continuous manner.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Assessing the believability of agents, characters and simulated actors is a core challenge for human computer interaction. While numerous approaches are suggested in the literature, they are all limited to discrete and low-granularity representations of believable behavior. In this paper we view believability, for the first time, as a time-continuous phenomenon and we explore the suitability of two different affect annotation schemes for its assessment. In particular, we study the degree to which we can predict character believability in a continuous fashion through a two-player game study. The game features various opponent behaviors that are assessed for their believability by 89 participants that played the game and then annotated their recorded playthrough. Random forest models are then trained to predict believability based on ad-hoc designed in-game features. Results suggest that a discrete annotation method leads to a more robust assessment of the ground truth and subsequently better modelling performance. Our best models are able to predict a change in perceived believability with a 72.5% accuracy on average (up to 90% in the best cases) in a time-continuous manner.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Assessing the believability of agents, characters and simulated actors is a core challenge for human computer interaction. While numerous approaches are suggested in the literature, they are all limited to discrete and low-granularity representations of believable behavior. In this paper we view believability, for the first time, as a time-continuous phenomenon and we explore the suitability of two different affect annotation schemes for its assessment. In particular, we study the degree to which we can predict character believability in a continuous fashion through a two-player game study. The game features various opponent behaviors that are assessed for their believability by 89 participants that played the game and then annotated their recorded playthrough. Random forest models are then trained to predict believability based on ad-hoc designed in-game features. Results suggest that a discrete annotation method leads to a more robust assessment of the ground truth and subsequently better modelling performance. Our best models are able to predict a change in perceived believability with a 72.5% accuracy on average (up to 90% in the best cases) in a time-continuous manner.",
"fno": "09597457",
"keywords": [
"Computer Games",
"Game Theory",
"Human Computer Interaction",
"Learning Artificial Intelligence",
"In Game Features",
"Discrete Annotation Method",
"Robust Assessment",
"Perceived Believability",
"Time Continuous Manner",
"Time Continuous Believability Prediction",
"Human Computer Interaction",
"Low Granularity Representations",
"Believable Behavior",
"Time Continuous Phenomenon",
"Character Believability",
"Continuous Fashion",
"Two Player Game Study",
"Affective Computing",
"Protocols",
"Correlation",
"Annotations",
"Computational Modeling",
"Games",
"Predictive Models",
"Believability",
"Human Like Agents",
"Preference Learning",
"Time Continuous Annotation",
"Digital Games"
],
"authors": [
{
"affiliation": "Queen Mary University of London,London,UK",
"fullName": "Cristiana Pacheco",
"givenName": "Cristiana",
"surname": "Pacheco",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Malta,Institute of Digital Games,Msida,Malta",
"fullName": "David Melhart",
"givenName": "David",
"surname": "Melhart",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Malta,Institute of Digital Games,Msida,Malta",
"fullName": "Antonios Liapis",
"givenName": "Antonios",
"surname": "Liapis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Malta,Institute of Digital Games,Msida,Malta",
"fullName": "Georgios N. Yannakakis",
"givenName": "Georgios N.",
"surname": "Yannakakis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Queen Mary University of London,London,UK",
"fullName": "Diego Perez-Liebana",
"givenName": "Diego",
"surname": "Perez-Liebana",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "acii",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-09-01T00:00:00",
"pubType": "proceedings",
"pages": "1-8",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-0019-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09597460",
"articleId": "1yylbtxovaE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09597428",
"articleId": "1yylbKvDwlO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/acii/2015/9953/0/07344680",
"title": "iHEARu-PLAY: Introducing a game for crowdsourced data collection for affective computing",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2015/07344680/12OmNAGepYd",
"parentPublication": {
"id": "proceedings/acii/2015/9953/0",
"title": "2015 International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2015/9953/0/07344648",
"title": "To rank or to classify? Annotating stress for reliable PTSD profiling",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2015/07344648/12OmNCbkQC4",
"parentPublication": {
"id": "proceedings/acii/2015/9953/0",
"title": "2015 International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2015/9953/0/07344627",
"title": "Grounding truth via ordinal annotation",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2015/07344627/12OmNvUaNgS",
"parentPublication": {
"id": "proceedings/acii/2015/9953/0",
"title": "2015 International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2017/0563/0/08273594",
"title": "RankTrace: Relative and unbounded affect annotation",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2017/08273594/12OmNyjtNHO",
"parentPublication": {
"id": "proceedings/acii/2017/0563/0",
"title": "2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2015/9953/0/07344628",
"title": "A socio-cognitive approach to personality: Machine-learned game strategies as cues of regulatory focus",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2015/07344628/12OmNzUPpCU",
"parentPublication": {
"id": "proceedings/acii/2015/9953/0",
"title": "2015 International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aciiw/2021/0021/0/09666288",
"title": "Discrete versus Ordinal Time-Continuous Believability Assessment",
"doi": null,
"abstractUrl": "/proceedings-article/aciiw/2021/09666288/1A3hNSZpZ8k",
"parentPublication": {
"id": "proceedings/aciiw/2021/0021/0",
"title": "2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/2022/04/09816018",
"title": "The Arousal Video Game AnnotatIoN (AGAIN) Dataset",
"doi": null,
"abstractUrl": "/journal/ta/2022/04/09816018/1EMUYPTHzIk",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aciiw/2022/5490/0/10085992",
"title": "The Invariant Ground Truth of Affect",
"doi": null,
"abstractUrl": "/proceedings-article/aciiw/2022/10085992/1M668WLwapq",
"parentPublication": {
"id": "proceedings/aciiw/2022/5490/0",
"title": "2022 10th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2019/3888/0/08925434",
"title": "PAGAN: Video Affect Annotation Made Easy",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2019/08925434/1fHGGyzDAKk",
"parentPublication": {
"id": "proceedings/acii/2019/3888/0",
"title": "2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/5555/01/09506939",
"title": "Werewolf-XL: A Database for Identifying Spontaneous Affect in Large Competitive Group Interactions",
"doi": null,
"abstractUrl": "/journal/ta/5555/01/09506939/1vNfhlFfMcw",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNrMHOd6",
"title": "2016 49th Hawaii International Conference on System Sciences (HICSS)",
"acronym": "hicss",
"groupId": "1000730",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwDSdd6",
"doi": "10.1109/HICSS.2016.184",
"title": "The Personal Equation of Interaction for Categorization of Composite Glyphs",
"normalizedTitle": "The Personal Equation of Interaction for Categorization of Composite Glyphs",
"abstract": "In this paper we advance the \"Personal Equation of Interaction\", examining individual differences between users that can be used to predict the accuracy of analysts' reasoning during visual analysis. We report 2 studies which expand the use of the Personal Equation of Interaction (PEI) beyond its current scope of predicting the accuracy of interface learning tasks to predicting the outcome of visio-cognitive object categorization. These studies extend the research of Yamauchi & Markman [3] using the dual learning theory of Ashby & Maddox [17]. Because visual reasoning is ubiquitous to the human experience and integral to big data visualization analysis, this research bridges the domain divide between psychological categorization theory and visual data analysis using composite glyphs. We define a psychometric measure that predicts the accuracy of composite glyph categorization and discuss its impact going forward.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper we advance the \"Personal Equation of Interaction\", examining individual differences between users that can be used to predict the accuracy of analysts' reasoning during visual analysis. We report 2 studies which expand the use of the Personal Equation of Interaction (PEI) beyond its current scope of predicting the accuracy of interface learning tasks to predicting the outcome of visio-cognitive object categorization. These studies extend the research of Yamauchi & Markman [3] using the dual learning theory of Ashby & Maddox [17]. Because visual reasoning is ubiquitous to the human experience and integral to big data visualization analysis, this research bridges the domain divide between psychological categorization theory and visual data analysis using composite glyphs. We define a psychometric measure that predicts the accuracy of composite glyph categorization and discuss its impact going forward.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper we advance the \"Personal Equation of Interaction\", examining individual differences between users that can be used to predict the accuracy of analysts' reasoning during visual analysis. We report 2 studies which expand the use of the Personal Equation of Interaction (PEI) beyond its current scope of predicting the accuracy of interface learning tasks to predicting the outcome of visio-cognitive object categorization. These studies extend the research of Yamauchi & Markman [3] using the dual learning theory of Ashby & Maddox [17]. Because visual reasoning is ubiquitous to the human experience and integral to big data visualization analysis, this research bridges the domain divide between psychological categorization theory and visual data analysis using composite glyphs. We define a psychometric measure that predicts the accuracy of composite glyph categorization and discuss its impact going forward.",
"fno": "5670b456",
"keywords": [
"Visualization",
"Data Visualization",
"Cognition",
"Pipelines",
"Image Color Analysis",
"Shape",
"Uncertainty"
],
"authors": [
{
"affiliation": null,
"fullName": "Tera Marie Greensmith",
"givenName": "Tera Marie",
"surname": "Greensmith",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "hicss",
"isOpenAccess": true,
"showRecommendedArticles": true,
"showBuyMe": false,
"hasPdf": true,
"pubDate": "2016-01-01T00:00:00",
"pubType": "proceedings",
"pages": "1456-1465",
"year": "2016",
"issn": "1530-1605",
"isbn": "978-0-7695-5670-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "5670b446",
"articleId": "12OmNAoUT2h",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "5670b466",
"articleId": "12OmNwDACl7",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/pacificvis/2018/1424/0/142401a116",
"title": "Composite Visual Mapping for Time Series Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2018/142401a116/12OmNCmpcJW",
"parentPublication": {
"id": "proceedings/pacificvis/2018/1424/0",
"title": "2018 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761599",
"title": "Layered object categorization",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761599/12OmNrMHOpp",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2015/8391/0/8391d943",
"title": "Learning a Discriminative Model for the Perception of Realism in Composite Images",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391d943/12OmNxAlA9f",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209a608",
"title": "Fine-Grained Visual Categorization with 2D-Warping",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209a608/12OmNxdVh0C",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iih-msp/2008/3278/0/3278b482",
"title": "Trust Evaluation Model for Composite Service Based on Subjective Logic",
"doi": null,
"abstractUrl": "/proceedings-article/iih-msp/2008/3278b482/12OmNyRxFsY",
"parentPublication": {
"id": "proceedings/iih-msp/2008/3278/0",
"title": "2008 Fourth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icci/2002/1724/0/17240229",
"title": "A Fuzzy Paradigm Approach for the Cognitive Process of Categorization",
"doi": null,
"abstractUrl": "/proceedings-article/icci/2002/17240229/12OmNzFv4iY",
"parentPublication": {
"id": "proceedings/icci/2002/1724/0",
"title": "Cognitive Informatics, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2012/2216/0/06460387",
"title": "Type-2 fuzzy labeled latent Dirichlet allocation for human action categorization",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460387/12OmNzlD9aO",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a058",
"title": "Visualizing Multidimensional Data in Treemaps with Adaptive Glyphs",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a058/17D45XeKgvR",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200k0265",
"title": "Benchmark Platform for Ultra-Fine-Grained Visual Categorization Beyond Human Performance",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200k0265/1BmFF1XfKLe",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300e587",
"title": "Learning Representational Invariance Instead of Categorization",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300e587/1i5mm3jL6p2",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNqBtj7T",
"title": "18th International Workshop on Database and Expert Systems Applications (DEXA 2007)",
"acronym": "dexa",
"groupId": "1000180",
"volume": "0",
"displayVolume": "0",
"year": "2007",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyTwRhZ",
"doi": "10.1109/DEXA.2007.137",
"title": "Incorporating Knowledge into e-Commerce Automated Negotiation",
"normalizedTitle": "Incorporating Knowledge into e-Commerce Automated Negotiation",
"abstract": "Challenges in e-Commerce negotiation reside in two issues such as, automation and knowledge incorporation. In this paper, we describe how knowledge plays a role in automated negotiation. A methodology that uses Knowledge Beads (KB) as knowledge representation that would be suitable for the design of automated negotiation systems is specified. KB helps in giving a unified approach for representing the data throughout the process that includes evaluation, negotiation, and postnegotiation. We classify the types of knowledge namely Contextual e-Commerce Knowledge and Negotiation knowledge, in the negotiation process.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Challenges in e-Commerce negotiation reside in two issues such as, automation and knowledge incorporation. In this paper, we describe how knowledge plays a role in automated negotiation. A methodology that uses Knowledge Beads (KB) as knowledge representation that would be suitable for the design of automated negotiation systems is specified. KB helps in giving a unified approach for representing the data throughout the process that includes evaluation, negotiation, and postnegotiation. We classify the types of knowledge namely Contextual e-Commerce Knowledge and Negotiation knowledge, in the negotiation process.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Challenges in e-Commerce negotiation reside in two issues such as, automation and knowledge incorporation. In this paper, we describe how knowledge plays a role in automated negotiation. A methodology that uses Knowledge Beads (KB) as knowledge representation that would be suitable for the design of automated negotiation systems is specified. KB helps in giving a unified approach for representing the data throughout the process that includes evaluation, negotiation, and postnegotiation. We classify the types of knowledge namely Contextual e-Commerce Knowledge and Negotiation knowledge, in the negotiation process.",
"fno": "29320600",
"keywords": [
"Automated Negotiation",
"Agents",
"Knowledge"
],
"authors": [
{
"affiliation": "University of Macau",
"fullName": "Zhuang Yan",
"givenName": "Zhuang",
"surname": "Yan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Macau",
"fullName": "Francis Yan",
"givenName": "Francis",
"surname": "Yan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Macau",
"fullName": "Simon Fong",
"givenName": "Simon",
"surname": "Fong",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dexa",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2007-09-01T00:00:00",
"pubType": "proceedings",
"pages": "600-604",
"year": "2007",
"issn": "1529-4188",
"isbn": "0-7695-2932-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "29320595",
"articleId": "12OmNCbCrRB",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "29320605",
"articleId": "12OmNxQOjHF",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fskd/2008/3305/1/3305a205",
"title": "Automated Negotiation Nased on Prioritised Fuzzy Constraint Satisfaction Problem",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2008/3305a205/12OmNB836PL",
"parentPublication": {
"id": "proceedings/fskd/2008/3305/1",
"title": "2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isbim/2008/3560/1/3560a194",
"title": "An Automated Mechanism for Negotiations in E-Commerce Systems",
"doi": null,
"abstractUrl": "/proceedings-article/isbim/2008/3560a194/12OmNCdk2zO",
"parentPublication": {
"id": "proceedings/isbim/2008/3560/1",
"title": "2008 International Seminar on Business and Information Management (ISBIM 2008)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iat/2004/2101/0/21010295",
"title": "Towards Genetically Optimised Responsive Negotiation Agents",
"doi": null,
"abstractUrl": "/proceedings-article/iat/2004/21010295/12OmNqBtiMI",
"parentPublication": {
"id": "proceedings/iat/2004/2101/0",
"title": "Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2004)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ncis/2011/4355/2/4355b024",
"title": "A Survey of Agent Based Automated Negotiation",
"doi": null,
"abstractUrl": "/proceedings-article/ncis/2011/4355b024/12OmNrHB1TU",
"parentPublication": {
"id": "proceedings/ncis/2011/4355/2",
"title": "Network Computing and Information Security, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/eee/2004/2073/0/20730421",
"title": "Knowledge Oriented Negotiation for Agent-Based B2B Electronic Commerce",
"doi": null,
"abstractUrl": "/proceedings-article/eee/2004/20730421/12OmNwBT1sr",
"parentPublication": {
"id": "proceedings/eee/2004/2073/0",
"title": "Proceedings. 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wgec/2009/3899/0/3899a177",
"title": "Using Ontology into Dynamic Electronic Negotiation Processes",
"doi": null,
"abstractUrl": "/proceedings-article/wgec/2009/3899a177/12OmNwF0BQf",
"parentPublication": {
"id": "proceedings/wgec/2009/3899/0",
"title": "Genetic and Evolutionary Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccgrid/2012/4691/0/4691a684",
"title": "On Effective Quality of Service Negotiation",
"doi": null,
"abstractUrl": "/proceedings-article/ccgrid/2012/4691a684/12OmNwK7o6U",
"parentPublication": {
"id": "proceedings/ccgrid/2012/4691/0",
"title": "Cluster Computing and the Grid, IEEE International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aici/2009/3816/4/3816d179",
"title": "Fuzzy Logic to Support Bilateral Agent Negotiation in E-commerce",
"doi": null,
"abstractUrl": "/proceedings-article/aici/2009/3816d179/12OmNxEjXVM",
"parentPublication": {
"id": "proceedings/aici/2009/3816/4",
"title": "2009 International Conference on Artificial Intelligence and Computational Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi/2007/3026/0/30260829",
"title": "A Model of B2B Negotiation using Knowledge",
"doi": null,
"abstractUrl": "/proceedings-article/wi/2007/30260829/12OmNzDNtrL",
"parentPublication": {
"id": "proceedings/wi/2007/3026/0",
"title": "2007 IEEE/WIC/ACM International Conference on Web Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iita/2009/3859/1/3859a419",
"title": "Simulation Study of Multi-Agent Based Automated Negotiation System in E-Commerce",
"doi": null,
"abstractUrl": "/proceedings-article/iita/2009/3859a419/12OmNzuIjqD",
"parentPublication": {
"id": "proceedings/iita/2009/3859/1",
"title": "2009 Third International Symposium on Intelligent Information Technology Application",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyQ7FQU",
"title": "Proceedings Visualization '93",
"acronym": "visual",
"groupId": "1000796",
"volume": "0",
"displayVolume": "0",
"year": "1993",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqNXEny",
"doi": "10.1109/VISUAL.1993.398845",
"title": "Fast volume rendering of compressed data",
"normalizedTitle": "Fast volume rendering of compressed data",
"abstract": "Volume rendering has been proposed as a useful tool for extracting information from large datasets, where non-visual analysis alone may not be feasible. The scale of these applications implies that data management is an important issue that needs to be addressed. Most volume rendering algorithms, however, process data in raw, uncompressed form. In previous work, we introduced a compressed volume format that may be volume rendered directly with minimal impact on rendering time. In this paper, we extend these ideas to a new volume format that not only reduces storage space and transmission time, but is designed for fast volume rendering as well. The volume dataset is represented as indices into a small codebook of representative blocks. With the data structure, volume shading calculations need only be performed on the codebook and image generation is accelerated by reusing precomputed block projections.<>",
"abstracts": [
{
"abstractType": "Regular",
"content": "Volume rendering has been proposed as a useful tool for extracting information from large datasets, where non-visual analysis alone may not be feasible. The scale of these applications implies that data management is an important issue that needs to be addressed. Most volume rendering algorithms, however, process data in raw, uncompressed form. In previous work, we introduced a compressed volume format that may be volume rendered directly with minimal impact on rendering time. In this paper, we extend these ideas to a new volume format that not only reduces storage space and transmission time, but is designed for fast volume rendering as well. The volume dataset is represented as indices into a small codebook of representative blocks. With the data structure, volume shading calculations need only be performed on the codebook and image generation is accelerated by reusing precomputed block projections.<>",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Volume rendering has been proposed as a useful tool for extracting information from large datasets, where non-visual analysis alone may not be feasible. The scale of these applications implies that data management is an important issue that needs to be addressed. Most volume rendering algorithms, however, process data in raw, uncompressed form. In previous work, we introduced a compressed volume format that may be volume rendered directly with minimal impact on rendering time. In this paper, we extend these ideas to a new volume format that not only reduces storage space and transmission time, but is designed for fast volume rendering as well. The volume dataset is represented as indices into a small codebook of representative blocks. With the data structure, volume shading calculations need only be performed on the codebook and image generation is accelerated by reusing precomputed block projections.",
"fno": "00398845",
"keywords": [
"Rendering Computer Graphics",
"Data Structures",
"Data Visualisation",
"Compressed Data",
"Large Datasets",
"Data Management",
"Algorithms",
"Storage Space",
"Transmission Time",
"Fast Volume Rendering",
"Indices",
"Codebook",
"Representative Blocks",
"Data Structure",
"Image Generation",
"Precomputed Block Projections",
"Rendering Computer Graphics",
"Data Visualization",
"Data Compression",
"Vector Quantization",
"Data Analysis",
"Speech Analysis",
"Image Storage",
"Isosurfaces",
"Ray Tracing",
"Data Mining"
],
"authors": [
{
"affiliation": "Dept. of Electr. Eng., Stanford Univ., CA, USA",
"fullName": "P. Ning",
"givenName": "P.",
"surname": "Ning",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Electr. Eng., Stanford Univ., CA, USA",
"fullName": "L. Hesselink",
"givenName": "L.",
"surname": "Hesselink",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "visual",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1993-01-01T00:00:00",
"pubType": "proceedings",
"pages": "11,12,13,14,15,16,17,18",
"year": "1993",
"issn": null,
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "00398833",
"articleId": "12OmNwGZNCk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "00398846",
"articleId": "12OmNy314f9",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-vis/2001/7200/0/7200pekar",
"title": "Fast Detection of Meaningful Isosurfaces for Volume Data Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2001/7200pekar/12OmNCbU3bR",
"parentPublication": {
"id": "proceedings/ieee-vis/2001/7200/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/1996/3673/0/36730049",
"title": "Fast Stereo Volume Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1996/36730049/12OmNqIhFPF",
"parentPublication": {
"id": "proceedings/ieee-vis/1996/3673/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vv/1998/9180/0/91800135",
"title": "Opacity-Weighted Color Interpolation, for Volume Sampling",
"doi": null,
"abstractUrl": "/proceedings-article/vv/1998/91800135/12OmNweBUMp",
"parentPublication": {
"id": "proceedings/vv/1998/9180/0",
"title": "Volume Visualization and Graphics, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/27660038",
"title": "Scale-Invariant Volume Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/27660038/12OmNxb5hu0",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/01532808",
"title": "Scale-invariant volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/01532808/12OmNyoAA5X",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/1995/7187/0/71870192",
"title": "Direct Rendering of Laplacian Pyramid Compressed Volume Data",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1995/71870192/12OmNzfXaty",
"parentPublication": {
"id": "proceedings/ieee-vis/1995/7187/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2003/2030/0/01250406",
"title": "Monte Carlo volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2003/01250406/12OmNzh5z86",
"parentPublication": {
"id": "proceedings/ieee-vis/2003/2030/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/02/ttg2010020273",
"title": "RACBVHs: Random-Accessible Compressed Bounding Volume Hierarchies",
"doi": null,
"abstractUrl": "/journal/tg/2010/02/ttg2010020273/13rRUwbs20S",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/06/ttg2012060925",
"title": "A Versatile Optical Model for Hybrid Rendering of Volume Data",
"doi": null,
"abstractUrl": "/journal/tg/2012/06/ttg2012060925/13rRUwjGoFX",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/1995/01/v0029",
"title": "Volume Rendering of DCT-Based Compressed 3D Scalar Data",
"doi": null,
"abstractUrl": "/journal/tg/1995/01/v0029/13rRUxZRbnP",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNynsbx3",
"title": "Visualization Conference, IEEE",
"acronym": "ieee-vis",
"groupId": "1000796",
"volume": "0",
"displayVolume": "0",
"year": "2003",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzh5z86",
"doi": "10.1109/VISUAL.2003.1250406",
"title": "Monte Carlo volume rendering",
"normalizedTitle": "Monte Carlo volume rendering",
"abstract": "In this paper a novel volume-rendering technique based on Monte Carlo integration is presented. As a result of a preprocessing, a point cloud of random samples is generated using a normalized continuous reconstruction of the volume as a probability density function. This point cloud is projected onto the image plane, and to each pixel an intensity value is assigned which is proportional to the number of samples projected onto the corresponding pixel area. In such a way a simulated X-ray image of the volume can be obtained. Theoretically, for a fixed image resolution, there exists an M number of samples such that the average standard deviation of the estimated pixel intensities us under the level of quantization error regardless of the number of voxels. Therefore Monte Carlo Volume Rendering (MCVR) is mainly proposed to efficiently visualize large volume data sets. Furthermore, network applications are also supported, since the trade-off between image quality and interactivity can be adapted to the bandwidth of the client/server connection by using progressive refinement.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper a novel volume-rendering technique based on Monte Carlo integration is presented. As a result of a preprocessing, a point cloud of random samples is generated using a normalized continuous reconstruction of the volume as a probability density function. This point cloud is projected onto the image plane, and to each pixel an intensity value is assigned which is proportional to the number of samples projected onto the corresponding pixel area. In such a way a simulated X-ray image of the volume can be obtained. Theoretically, for a fixed image resolution, there exists an M number of samples such that the average standard deviation of the estimated pixel intensities us under the level of quantization error regardless of the number of voxels. Therefore Monte Carlo Volume Rendering (MCVR) is mainly proposed to efficiently visualize large volume data sets. Furthermore, network applications are also supported, since the trade-off between image quality and interactivity can be adapted to the bandwidth of the client/server connection by using progressive refinement.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper a novel volume-rendering technique based on Monte Carlo integration is presented. As a result of a preprocessing, a point cloud of random samples is generated using a normalized continuous reconstruction of the volume as a probability density function. This point cloud is projected onto the image plane, and to each pixel an intensity value is assigned which is proportional to the number of samples projected onto the corresponding pixel area. In such a way a simulated X-ray image of the volume can be obtained. Theoretically, for a fixed image resolution, there exists an M number of samples such that the average standard deviation of the estimated pixel intensities us under the level of quantization error regardless of the number of voxels. Therefore Monte Carlo Volume Rendering (MCVR) is mainly proposed to efficiently visualize large volume data sets. Furthermore, network applications are also supported, since the trade-off between image quality and interactivity can be adapted to the bandwidth of the client/server connection by using progressive refinement.",
"fno": "01250406",
"keywords": [
"Rendering Computer Graphics",
"Monte Carlo Methods",
"Probability",
"Image Processing",
"Monte Carlo Volume Rendering",
"Monte Carlo Integration",
"Volume Reconstruction",
"Probability Density Function",
"X Ray Image",
"Image Resolution",
"Pixel Intensity",
"Quantization Error",
"Monte Carlo Volume Rendering",
"MCVR",
"Image Quality",
"Image Interactivity",
"Client Server Connection",
"Progressive Refinement",
"Monte Carlo Methods",
"Pixel",
"Rendering Computer Graphics",
"Clouds",
"Image Reconstruction",
"Probability Density Function",
"X Ray Imaging",
"Image Resolution",
"Quantization",
"Data Visualization"
],
"authors": [
{
"affiliation": "Dept. of Control Eng. & Inf. Technol., Budapest Tech. Univ., Hungary",
"fullName": "B. Csebfalvi",
"givenName": "B.",
"surname": "Csebfalvi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Control Eng. & Inf. Technol., Budapest Tech. Univ., Hungary",
"fullName": "L. Szirmay-Kalos",
"givenName": "L.",
"surname": "Szirmay-Kalos",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ieee-vis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2003-01-01T00:00:00",
"pubType": "proceedings",
"pages": "449-456",
"year": "2003",
"issn": null,
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "20300040",
"articleId": "12OmNxEjY0A",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "20300041",
"articleId": "12OmNzRHOMw",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/vv/2000/308/0/04384235",
"title": "Accelerating Volume Rendering with Quantized Voxels",
"doi": null,
"abstractUrl": "/proceedings-article/vv/2000/04384235/12OmNAndifp",
"parentPublication": {
"id": "proceedings/vv/2000/308/0",
"title": "2000 IEEE Symposium on Volume Visualization (VV 2000)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/visapp/2014/8133/1/07294835",
"title": "Monte-Carlo image retargeting",
"doi": null,
"abstractUrl": "/proceedings-article/visapp/2014/07294835/12OmNBCqbA4",
"parentPublication": {
"id": "proceedings/visapp/2014/8133/1",
"title": "2014 International Conference on Computer Vision Theory and Applications (VISAPP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2006/2746/0/274600734",
"title": "Volume Rendering Using Tiny Particles",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2006/274600734/12OmNBubOVy",
"parentPublication": {
"id": "proceedings/ism/2006/2746/0",
"title": "Eighth IEEE International Symposium on Multimedia (ISM'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2003/2030/0/20300059",
"title": "Monte Carlo Volume Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2003/20300059/12OmNCdBDFe",
"parentPublication": {
"id": "proceedings/ieee-vis/2003/2030/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apvis/2007/0808/0/04126230",
"title": "Particle-based volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/apvis/2007/04126230/12OmNCeaPW4",
"parentPublication": {
"id": "proceedings/apvis/2007/0808/0",
"title": "Asia-Pacific Symposium on Visualisation 2007",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vv/2004/8781/0/87810033",
"title": "Interactive Transfer Function Control for Monte Carlo Volume Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/vv/2004/87810033/12OmNwGqBoE",
"parentPublication": {
"id": "proceedings/vv/2004/8781/0",
"title": "Volume Visualization and Graphics, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2015/7673/0/7673a125",
"title": "Detection and Removal for Impulse Noise in Monte Carlo Global Illumination Rendered Images of Highly Glossy Scenes",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2015/7673a125/12OmNwcCIOj",
"parentPublication": {
"id": "proceedings/icvrv/2015/7673/0",
"title": "2015 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761633",
"title": "An adaptive Monte Carlo approach to nonlinear image denoising",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761633/12OmNzBOiip",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761753",
"title": "Point-based digitally reconstructed radiograph",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761753/12OmNzICEJb",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/1990/02/mcg1990020033",
"title": "Volume Rendering",
"doi": null,
"abstractUrl": "/magazine/cg/1990/02/mcg1990020033/13rRUwcAquw",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzuZUzq",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"acronym": "icdm",
"groupId": "1000179",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAlvHTi",
"doi": "10.1109/ICDM.2016.0187",
"title": "Gaussian Component Based Index for GMMs",
"normalizedTitle": "Gaussian Component Based Index for GMMs",
"abstract": "Efficient similarity search for uncertain data is a challenging task in many modern data mining applications like image retrieval, speaker recognition and stock market analysis. A common way to model the uncertainty of data objects is using probability density functions in the form of Gaussian Mixture Models (GMMs), which have an ability to approximate arbitrary distribution. However, due to the possible unequal length of mixture models, the use of existing index techniques has serious problems for the objects modeled by GMMs. Either the techniques cannot handle GMMs or they have too many limitations. Hence, we propose a dynamic index structure, Gaussian Component based Index (GCI), for GMMs. GCI decomposes GMMs into the single, pairs, or n-lets of Gaussian components, stores these components into well studied index trees such as U-tree and Gauss-Tree, and refines the corresponding GMMs in a conservative but tight way. GCI supports both k-most-likely queries and probability threshold queries by means of Matching Probability. Extensive experimental evaluations of GCI demonstrate a considerable speed-up of similarity search on both synthetic and real-world data sets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Efficient similarity search for uncertain data is a challenging task in many modern data mining applications like image retrieval, speaker recognition and stock market analysis. A common way to model the uncertainty of data objects is using probability density functions in the form of Gaussian Mixture Models (GMMs), which have an ability to approximate arbitrary distribution. However, due to the possible unequal length of mixture models, the use of existing index techniques has serious problems for the objects modeled by GMMs. Either the techniques cannot handle GMMs or they have too many limitations. Hence, we propose a dynamic index structure, Gaussian Component based Index (GCI), for GMMs. GCI decomposes GMMs into the single, pairs, or n-lets of Gaussian components, stores these components into well studied index trees such as U-tree and Gauss-Tree, and refines the corresponding GMMs in a conservative but tight way. GCI supports both k-most-likely queries and probability threshold queries by means of Matching Probability. Extensive experimental evaluations of GCI demonstrate a considerable speed-up of similarity search on both synthetic and real-world data sets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Efficient similarity search for uncertain data is a challenging task in many modern data mining applications like image retrieval, speaker recognition and stock market analysis. A common way to model the uncertainty of data objects is using probability density functions in the form of Gaussian Mixture Models (GMMs), which have an ability to approximate arbitrary distribution. However, due to the possible unequal length of mixture models, the use of existing index techniques has serious problems for the objects modeled by GMMs. Either the techniques cannot handle GMMs or they have too many limitations. Hence, we propose a dynamic index structure, Gaussian Component based Index (GCI), for GMMs. GCI decomposes GMMs into the single, pairs, or n-lets of Gaussian components, stores these components into well studied index trees such as U-tree and Gauss-Tree, and refines the corresponding GMMs in a conservative but tight way. GCI supports both k-most-likely queries and probability threshold queries by means of Matching Probability. Extensive experimental evaluations of GCI demonstrate a considerable speed-up of similarity search on both synthetic and real-world data sets.",
"fno": "07838000",
"keywords": [
"Data Mining",
"Gaussian Processes",
"Mixture Models",
"Probability",
"Query Processing",
"Statistical Distributions",
"Trees Mathematics",
"Gaussian Component Based Index Techniques",
"GM Ms",
"Similarity Search",
"Uncertain Data",
"Data Mining",
"Data Object Uncertainty",
"Probability Density Functions",
"Gaussian Mixture Models",
"Dynamic Index Structure",
"GCI",
"U Tree",
"Gauss Tree",
"Index Trees",
"K Most Likely Query",
"Probability Threshold Query",
"Matching Probability",
"Indexes",
"Probability Density Function",
"Gaussian Mixture Model",
"Gaussian Distribution",
"Covariance Matrices",
"Mixture Models"
],
"authors": [
{
"affiliation": null,
"fullName": "Linfei Zhou",
"givenName": "Linfei",
"surname": "Zhou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Bianca Wackersreuther",
"givenName": "Bianca",
"surname": "Wackersreuther",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Frank Fiedler",
"givenName": "Frank",
"surname": "Fiedler",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Claudia Plant",
"givenName": "Claudia",
"surname": "Plant",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Christian Böhm",
"givenName": "Christian",
"surname": "Böhm",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-12-01T00:00:00",
"pubType": "proceedings",
"pages": "1365-1370",
"year": "2016",
"issn": "2374-8486",
"isbn": "978-1-5090-5473-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "07837999",
"articleId": "12OmNwCaCpH",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07838001",
"articleId": "12OmNrGb2iP",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/acssc/1997/8316/2/00679183",
"title": "Small sample properties of the RSS estimation algorithm for Gaussian measurement noise",
"doi": null,
"abstractUrl": "/proceedings-article/acssc/1997/00679183/12OmNASILWu",
"parentPublication": {
"id": "proceedings/acssc/1997/8316/2",
"title": "Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36163)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/avss/2012/4797/0/4797a368",
"title": "Pairwise Threshold for Gaussian Mixture Classification and Its Application on Human Tracking Enhancement",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2012/4797a368/12OmNAle6D5",
"parentPublication": {
"id": "proceedings/avss/2012/4797/0",
"title": "2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2012/4747/0/4747a246",
"title": "Searching Uncertain Data Represented by Non-axis Parallel Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2012/4747a246/12OmNBEGYKH",
"parentPublication": {
"id": "proceedings/icde/2012/4747/0",
"title": "2012 IEEE 28th International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bracis/2015/0016/0/0016a055",
"title": "IGMM-CD: A Gaussian Mixture Classification Algorithm for Data Streams with Concept Drifts",
"doi": null,
"abstractUrl": "/proceedings-article/bracis/2015/0016a055/12OmNvjgWQT",
"parentPublication": {
"id": "proceedings/bracis/2015/0016/0",
"title": "2015 Brazilian Conference on Intelligent Systems (BRACIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2011/4409/0/4409a286",
"title": "Parametric Characterization of Multimodal Distributions with Non-gaussian Modes",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2011/4409a286/12OmNwl8GID",
"parentPublication": {
"id": "proceedings/icdmw/2011/4409/0",
"title": "2011 IEEE 11th International Conference on Data Mining Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/spw/2017/1968/0/1968a229",
"title": "Using Gaussian Mixture Models to Detect Outliers in Seasonal Univariate Network Traffic",
"doi": null,
"abstractUrl": "/proceedings-article/spw/2017/1968a229/12OmNyRPgz6",
"parentPublication": {
"id": "proceedings/spw/2017/1968/0",
"title": "2017 IEEE Security and Privacy Workshops (SPW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2015/8391/0/8391c884",
"title": "Interpolation on the Manifold of K Component GMMs",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391c884/12OmNzC5T1f",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2011/09/ttk2011091406",
"title": "Laplacian Regularized Gaussian Mixture Model for Data Clustering",
"doi": null,
"abstractUrl": "/journal/tk/2011/09/ttk2011091406/13rRUxBa5xB",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2017/11/07938761",
"title": "A Fully-Pipelined Hardware Design for Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tc/2017/11/07938761/13rRUxjQyoA",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903677",
"title": "GRay: Ray Casting for Visualization and Interactive Data Exploration of Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903677/1GZoj8mhSPS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzwpUa5",
"title": "2012 IEEE 28th International Conference on Data Engineering",
"acronym": "icde",
"groupId": "1000178",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBEGYKH",
"doi": "10.1109/ICDE.2012.7",
"title": "Searching Uncertain Data Represented by Non-axis Parallel Gaussian Mixture Models",
"normalizedTitle": "Searching Uncertain Data Represented by Non-axis Parallel Gaussian Mixture Models",
"abstract": "Efficient similarity search in uncertain data is a central problem in many modern applications such as biometric identification, stock market analysis, sensor networks, medical imaging, etc. In such applications, the feature vector of an object is not exactly known but is rather defined by a probability density function like a Gaussian Mixture Model (GMM). Previous work is limited to axis-parallel Gaussian distributions, hence, correlations between different features are not considered in the similarity search. In this paper, we propose a novel, efficient similarity search technique for general GMMs without independence assumption for the attributes, named SUDN, which approximates the actual components of a GMM in a conservative but tight way. A filter-refinement architecture guarantees no false dismissals, due to conservativity, as well as a good filter selectivity, due to the tightness of our approximations. An extensive experimental evaluation of SUDN demonstrates a considerable speed-up of similarity queries on general GMMs and an increase in accuracy compared to existing approaches.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Efficient similarity search in uncertain data is a central problem in many modern applications such as biometric identification, stock market analysis, sensor networks, medical imaging, etc. In such applications, the feature vector of an object is not exactly known but is rather defined by a probability density function like a Gaussian Mixture Model (GMM). Previous work is limited to axis-parallel Gaussian distributions, hence, correlations between different features are not considered in the similarity search. In this paper, we propose a novel, efficient similarity search technique for general GMMs without independence assumption for the attributes, named SUDN, which approximates the actual components of a GMM in a conservative but tight way. A filter-refinement architecture guarantees no false dismissals, due to conservativity, as well as a good filter selectivity, due to the tightness of our approximations. An extensive experimental evaluation of SUDN demonstrates a considerable speed-up of similarity queries on general GMMs and an increase in accuracy compared to existing approaches.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Efficient similarity search in uncertain data is a central problem in many modern applications such as biometric identification, stock market analysis, sensor networks, medical imaging, etc. In such applications, the feature vector of an object is not exactly known but is rather defined by a probability density function like a Gaussian Mixture Model (GMM). Previous work is limited to axis-parallel Gaussian distributions, hence, correlations between different features are not considered in the similarity search. In this paper, we propose a novel, efficient similarity search technique for general GMMs without independence assumption for the attributes, named SUDN, which approximates the actual components of a GMM in a conservative but tight way. A filter-refinement architecture guarantees no false dismissals, due to conservativity, as well as a good filter selectivity, due to the tightness of our approximations. An extensive experimental evaluation of SUDN demonstrates a considerable speed-up of similarity queries on general GMMs and an increase in accuracy compared to existing approaches.",
"fno": "4747a246",
"keywords": [
"Similarity Search",
"Uncertain Data",
"Gaussian Mixture Model",
"Non Axis Parallel GMM",
"MLIQ"
],
"authors": [
{
"affiliation": null,
"fullName": "Katrin Haegler",
"givenName": "Katrin",
"surname": "Haegler",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Frank Fiedler",
"givenName": "Frank",
"surname": "Fiedler",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Christian Böhm",
"givenName": "Christian",
"surname": "Böhm",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icde",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-04-01T00:00:00",
"pubType": "proceedings",
"pages": "246-257",
"year": "2012",
"issn": "1084-4627",
"isbn": "978-0-7695-4747-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4747a234",
"articleId": "12OmNwErpz8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4747a258",
"articleId": "12OmNBE7Muq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/avss/2012/4797/0/4797a368",
"title": "Pairwise Threshold for Gaussian Mixture Classification and Its Application on Human Tracking Enhancement",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2012/4797a368/12OmNAle6D5",
"parentPublication": {
"id": "proceedings/avss/2012/4797/0",
"title": "2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2016/5473/0/07838000",
"title": "Gaussian Component Based Index for GMMs",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2016/07838000/12OmNAlvHTi",
"parentPublication": {
"id": "proceedings/icdm/2016/5473/0",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2011/4584/0/4584b357",
"title": "Similarity Matching over Uncertain Time Series",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2011/4584b357/12OmNqH9hdK",
"parentPublication": {
"id": "proceedings/cis/2011/4584/0",
"title": "2011 Seventh International Conference on Computational Intelligence and Security",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icesssymposia/2008/3288/0/3288a441",
"title": "Frequency and Space Domain Features for Image Classification Using Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icesssymposia/2008/3288a441/12OmNrkjVhj",
"parentPublication": {
"id": "proceedings/icesssymposia/2008/3288/0",
"title": "Embedded Software and Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pcspa/2010/4180/0/4180a964",
"title": "Algorithm to Unmixing Hyperspectral Images Based on APSO-GMM",
"doi": null,
"abstractUrl": "/proceedings-article/pcspa/2010/4180a964/12OmNvlPkGf",
"parentPublication": {
"id": "proceedings/pcspa/2010/4180/0",
"title": "Pervasive Computing, Signal Porcessing and Applications, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdcat/2011/4564/0/4564a167",
"title": "Fast Estimation of Gaussian Mixture Model Parameters on GPU Using CUDA",
"doi": null,
"abstractUrl": "/proceedings-article/pdcat/2011/4564a167/12OmNxeut3p",
"parentPublication": {
"id": "proceedings/pdcat/2011/4564/0",
"title": "Parallel and Distributed Computing Applications and Technologies, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/spw/2017/1968/0/1968a229",
"title": "Using Gaussian Mixture Models to Detect Outliers in Seasonal Univariate Network Traffic",
"doi": null,
"abstractUrl": "/proceedings-article/spw/2017/1968a229/12OmNyRPgz6",
"parentPublication": {
"id": "proceedings/spw/2017/1968/0",
"title": "2017 IEEE Security and Privacy Workshops (SPW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icapr/2009/3520/0/3520a047",
"title": "Model Based Clustering of Audio Clips Using Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icapr/2009/3520a047/12OmNzTppDx",
"parentPublication": {
"id": "proceedings/icapr/2009/3520/0",
"title": "Advances in Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2010/4109/0/4109d623",
"title": "Low-Level Image Segmentation Based Scene Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2010/4109d623/12OmNzlD9sd",
"parentPublication": {
"id": "proceedings/icpr/2010/4109/0",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2017/11/07938761",
"title": "A Fully-Pipelined Hardware Design for Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tc/2017/11/07938761/13rRUxjQyoA",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNvTBBbx",
"title": "Intelligent Networks and Intelligent Systems, International Workshop on",
"acronym": "icinis",
"groupId": "1002524",
"volume": "0",
"displayVolume": "0",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNCd2rFh",
"doi": "10.1109/ICINIS.2009.89",
"title": "Player Detection Algorithm Based on Gaussian Mixture Models Background Modeling",
"normalizedTitle": "Player Detection Algorithm Based on Gaussian Mixture Models Background Modeling",
"abstract": "Most proposed methods of detecting moving objects can not segment the players in soccer videos well. In this paper, we present a novel background subtraction algorithm based on Gaussian Mixture Models (GMMs). In the initial stage, we pre-process the frame with compensation construction method we propose. In the updating stage, the moving area and background one can be classified by differencing two consecutive frames. According to the special area, we update the GMMs with corresponding rate. Experimental results show that our algorithms are effective in detecting moving objects in the dynamic scene.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Most proposed methods of detecting moving objects can not segment the players in soccer videos well. In this paper, we present a novel background subtraction algorithm based on Gaussian Mixture Models (GMMs). In the initial stage, we pre-process the frame with compensation construction method we propose. In the updating stage, the moving area and background one can be classified by differencing two consecutive frames. According to the special area, we update the GMMs with corresponding rate. Experimental results show that our algorithms are effective in detecting moving objects in the dynamic scene.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Most proposed methods of detecting moving objects can not segment the players in soccer videos well. In this paper, we present a novel background subtraction algorithm based on Gaussian Mixture Models (GMMs). In the initial stage, we pre-process the frame with compensation construction method we propose. In the updating stage, the moving area and background one can be classified by differencing two consecutive frames. According to the special area, we update the GMMs with corresponding rate. Experimental results show that our algorithms are effective in detecting moving objects in the dynamic scene.",
"fno": "3852a323",
"keywords": [
"Background Modeling",
"Gaussian Mixture Model",
"Player Detection",
"Frames Difference"
],
"authors": [
{
"affiliation": null,
"fullName": "Yu Ming",
"givenName": "Yu",
"surname": "Ming",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Cui Guodong",
"givenName": "Cui",
"surname": "Guodong",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Qi Lichao",
"givenName": "Qi",
"surname": "Lichao",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icinis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-11-01T00:00:00",
"pubType": "proceedings",
"pages": "323-326",
"year": "2009",
"issn": null,
"isbn": "978-0-7695-3852-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3852a319",
"articleId": "12OmNCcKQkg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3852a327",
"articleId": "12OmNqIzh69",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ism/2012/4875/0/4875a360",
"title": "Spatio-temporal Gaussian Mixture Model for Background Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2012/4875a360/12OmNBpEeKI",
"parentPublication": {
"id": "proceedings/ism/2012/4875/0",
"title": "2012 IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csa/2015/9961/0/9961a168",
"title": "Hand Segmentation Based on Improved Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/csa/2015/9961a168/12OmNC4O4Fc",
"parentPublication": {
"id": "proceedings/csa/2015/9961/0",
"title": "2015 International Conference on Computer Science and Applications (CSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2008/3381/0/3381a730",
"title": "An Improved Mixture Gaussian Models to Detect Moving Object Under Real-Time Complex Background",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2008/3381a730/12OmNs4S8BI",
"parentPublication": {
"id": "proceedings/cw/2008/3381/0",
"title": "2008 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wgec/2009/3899/0/3899a331",
"title": "Video Background Extraction Based on Improved Mode Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/wgec/2009/3899a331/12OmNvDqsOu",
"parentPublication": {
"id": "proceedings/wgec/2009/3899/0",
"title": "Genetic and Evolutionary Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/avss/2011/0844/0/06027356",
"title": "Speeded up Gaussian Mixture Model algorithm for background subtraction",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2011/06027356/12OmNweBUFE",
"parentPublication": {
"id": "proceedings/avss/2011/0844/0",
"title": "2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iwcse/2009/3881/1/3881a347",
"title": "Moving Object Detection Algorithm Based on Variance Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/iwcse/2009/3881a347/12OmNxR5UJB",
"parentPublication": {
"id": "proceedings/iwcse/2009/3881/1",
"title": "Computer Science and Engineering, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/spw/2017/1968/0/1968a229",
"title": "Using Gaussian Mixture Models to Detect Outliers in Seasonal Univariate Network Traffic",
"doi": null,
"abstractUrl": "/proceedings-article/spw/2017/1968a229/12OmNyRPgz6",
"parentPublication": {
"id": "proceedings/spw/2017/1968/0",
"title": "2017 IEEE Security and Privacy Workshops (SPW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mediacom/2010/4136/0/4136a090",
"title": "An Improved Foreground Object Detection Method Based on Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/mediacom/2010/4136a090/12OmNzd7bE0",
"parentPublication": {
"id": "proceedings/mediacom/2010/4136/0",
"title": "2010 International Conference on Multimedia Communications (Mediacom 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/crv/2019/1838/0/183800a025",
"title": "Direct Fitting of Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/crv/2019/183800a025/1cMGuFJMJna",
"parentPublication": {
"id": "proceedings/crv/2019/1838/0",
"title": "2019 16th Conference on Computer and Robot Vision (CRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAY79o8",
"title": "Embedded Software and Systems, International Conference on",
"acronym": "icesssymposia",
"groupId": "1002448",
"volume": "0",
"displayVolume": "0",
"year": "2008",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNrkjVhj",
"doi": "10.1109/ICESS.Symposia.2008.33",
"title": "Frequency and Space Domain Features for Image Classification Using Gaussian Mixture Models",
"normalizedTitle": "Frequency and Space Domain Features for Image Classification Using Gaussian Mixture Models",
"abstract": "This paper presents an effective combination of Wavelet-based features and SIFT features, both of them have the frequency domain and space domain information characteristic. For the combined feature patches extracted from images we then adopt the PCA transformation to reduce the dimensionality of their feature vectors. And the reduced vectors are used to train Gaussian Mixture Models (GMMs) in which the mixture weights are adjusted iteratively. We experiment on Caltech datasets using this enhanced method, and the results comparing with several other methods show that the combination of salient feature vectors and GMM gives a much better improvement in image classification.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents an effective combination of Wavelet-based features and SIFT features, both of them have the frequency domain and space domain information characteristic. For the combined feature patches extracted from images we then adopt the PCA transformation to reduce the dimensionality of their feature vectors. And the reduced vectors are used to train Gaussian Mixture Models (GMMs) in which the mixture weights are adjusted iteratively. We experiment on Caltech datasets using this enhanced method, and the results comparing with several other methods show that the combination of salient feature vectors and GMM gives a much better improvement in image classification.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents an effective combination of Wavelet-based features and SIFT features, both of them have the frequency domain and space domain information characteristic. For the combined feature patches extracted from images we then adopt the PCA transformation to reduce the dimensionality of their feature vectors. And the reduced vectors are used to train Gaussian Mixture Models (GMMs) in which the mixture weights are adjusted iteratively. We experiment on Caltech datasets using this enhanced method, and the results comparing with several other methods show that the combination of salient feature vectors and GMM gives a much better improvement in image classification.",
"fno": "3288a441",
"keywords": [
"Image Classification",
"Gaussian Mixture Models",
"Feature Extraction"
],
"authors": [
{
"affiliation": null,
"fullName": "Bin Fu",
"givenName": "Bin",
"surname": "Fu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Zhen Ren",
"givenName": "Zhen",
"surname": "Ren",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icesssymposia",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2008-07-01T00:00:00",
"pubType": "proceedings",
"pages": "441-446",
"year": "2008",
"issn": null,
"isbn": "978-0-7695-3288-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3288a437",
"articleId": "12OmNxd4twZ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3288a453",
"articleId": "12OmNBpmDJO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/avss/2012/4797/0/4797a368",
"title": "Pairwise Threshold for Gaussian Mixture Classification and Its Application on Human Tracking Enhancement",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2012/4797a368/12OmNAle6D5",
"parentPublication": {
"id": "proceedings/avss/2012/4797/0",
"title": "2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2016/5473/0/07838000",
"title": "Gaussian Component Based Index for GMMs",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2016/07838000/12OmNAlvHTi",
"parentPublication": {
"id": "proceedings/icdm/2016/5473/0",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2012/4747/0/4747a246",
"title": "Searching Uncertain Data Represented by Non-axis Parallel Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2012/4747a246/12OmNBEGYKH",
"parentPublication": {
"id": "proceedings/icde/2012/4747/0",
"title": "2012 IEEE 28th International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icinis/2009/3852/0/3852a323",
"title": "Player Detection Algorithm Based on Gaussian Mixture Models Background Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/icinis/2009/3852a323/12OmNCd2rFh",
"parentPublication": {
"id": "proceedings/icinis/2009/3852/0",
"title": "Intelligent Networks and Intelligent Systems, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2016/7258/0/07552867",
"title": "Robust image matching via feature guided Gaussian mixture model",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2016/07552867/12OmNrEL2zl",
"parentPublication": {
"id": "proceedings/icme/2016/7258/0",
"title": "2016 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iih-msp/2008/3278/0/3278a079",
"title": "Combination of Wavelet snd SIFT Features for Image Classification Using Trained Gaussion Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/iih-msp/2008/3278a079/12OmNvrvjc5",
"parentPublication": {
"id": "proceedings/iih-msp/2008/3278/0",
"title": "2008 Fourth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dexa/2007/2932/0/29320099",
"title": "Automatic Genre Classification of TV Programmes Using Gaussian Mixture Models and Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/dexa/2007/29320099/12OmNzyGH5Y",
"parentPublication": {
"id": "proceedings/dexa/2007/2932/0",
"title": "18th International Workshop on Database and Expert Systems Applications (DEXA 2007)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2011/09/ttk2011091406",
"title": "Laplacian Regularized Gaussian Mixture Model for Data Clustering",
"doi": null,
"abstractUrl": "/journal/tk/2011/09/ttk2011091406/13rRUxBa5xB",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903677",
"title": "GRay: Ray Casting for Visualization and Interactive Data Exploration of Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903677/1GZoj8mhSPS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/crv/2019/1838/0/183800a025",
"title": "Direct Fitting of Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/crv/2019/183800a025/1cMGuFJMJna",
"parentPublication": {
"id": "proceedings/crv/2019/1838/0",
"title": "2019 16th Conference on Computer and Robot Vision (CRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNwBjP17",
"title": "2016 8th International Conference on Information Technology in Medicine and Education (ITME)",
"acronym": "itme",
"groupId": "1002567",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwBT1mL",
"doi": "10.1109/ITME.2016.0139",
"title": "Maximum Gaussian Mixture Model for Classification",
"normalizedTitle": "Maximum Gaussian Mixture Model for Classification",
"abstract": "There are a variety of models and algorithms that solves classification problems. Among these models, Maximum Gaussian Mixture Model (MGMM) is a model we proposed earlier that describes data using the maximum value of Gaussians. Expectation Maximization (EM) algorithm can be used to solve this model. In this paper, we propose a multiEM approach to solve MGMM and to train MGMM based classifiers. This approach combines multiple MGMMs solved by EM into a classifier. The classifiers trained with this approach on both artificial and real life datasets were tested to have good performance with 10-fold cross validation.",
"abstracts": [
{
"abstractType": "Regular",
"content": "There are a variety of models and algorithms that solves classification problems. Among these models, Maximum Gaussian Mixture Model (MGMM) is a model we proposed earlier that describes data using the maximum value of Gaussians. Expectation Maximization (EM) algorithm can be used to solve this model. In this paper, we propose a multiEM approach to solve MGMM and to train MGMM based classifiers. This approach combines multiple MGMMs solved by EM into a classifier. The classifiers trained with this approach on both artificial and real life datasets were tested to have good performance with 10-fold cross validation.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "There are a variety of models and algorithms that solves classification problems. Among these models, Maximum Gaussian Mixture Model (MGMM) is a model we proposed earlier that describes data using the maximum value of Gaussians. Expectation Maximization (EM) algorithm can be used to solve this model. In this paper, we propose a multiEM approach to solve MGMM and to train MGMM based classifiers. This approach combines multiple MGMMs solved by EM into a classifier. The classifiers trained with this approach on both artificial and real life datasets were tested to have good performance with 10-fold cross validation.",
"fno": "3906a587",
"keywords": [
"Expectation Maximisation Algorithm",
"Gaussian Processes",
"Mixture Models",
"Pattern Classification",
"MGMM Based Classifiers",
"Multi EM Approach",
"EM Algorithm",
"Expectation Maximization Algorithm",
"Classification",
"Maximum Gaussian Mixture Model",
"Gaussian Mixture Model",
"Ionosphere",
"Algorithm Design And Analysis",
"Covariance Matrices",
"Cancer",
"Computational Modeling",
"Classification",
"Maximum Gaussian Mixture Model"
],
"authors": [
{
"affiliation": "Dept. of Comput. Sci. & Software Eng., Xi'an Jiaotong-Liverpool Univ., Suzhou, China",
"fullName": "Jiehao Zhang",
"givenName": "Jiehao",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci. & Software Eng., Xi'an Jiaotong-Liverpool Univ., Suzhou, China",
"fullName": "Xianbin Hong",
"givenName": "Xianbin",
"surname": "Hong",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci. & Software Eng., Xi'an Jiaotong-Liverpool Univ., Suzhou, China",
"fullName": "Sheng-Uei Guan",
"givenName": "Sheng-Uei",
"surname": "Guan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci. & Software Eng., Xi'an Jiaotong-Liverpool Univ., Suzhou, China",
"fullName": "Xuan Zhao",
"givenName": "Xuan",
"surname": "Zhao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci. & Software Eng., Xi'an Jiaotong-Liverpool Univ., Suzhou, China",
"fullName": "Huang Xin",
"givenName": "Huang",
"surname": "Xin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci. & Software Eng., Xi'an Jiaotong-Liverpool Univ., Suzhou, China",
"fullName": "Nian Xue",
"givenName": "Nian",
"surname": "Xue",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "itme",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-12-01T00:00:00",
"pubType": "proceedings",
"pages": "587-591",
"year": "2016",
"issn": "2474-3828",
"isbn": "978-1-5090-3906-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3906a584",
"articleId": "12OmNwwMf1F",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3906a592",
"articleId": "12OmNzfXauk",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icnc/2009/3736/6/3736f479",
"title": "A Novel Split and Merge EM Algorithm for Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2009/3736f479/12OmNAWH9FQ",
"parentPublication": {
"id": "proceedings/icnc/2009/3736/6",
"title": "2009 Fifth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2016/7258/0/07552867",
"title": "Robust image matching via feature guided Gaussian mixture model",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2016/07552867/12OmNrEL2zl",
"parentPublication": {
"id": "proceedings/icme/2016/7258/0",
"title": "2016 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2017/3581/0/3581a704",
"title": "A Comparison Between Different Gaussian-Based Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2017/3581a704/12OmNwLOYWp",
"parentPublication": {
"id": "proceedings/aiccsa/2017/3581/0",
"title": "2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2010/4109/0/4109a746",
"title": "Maximum Likelihood Estimation of Gaussian Mixture Models Using Particle Swarm Optimization",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2010/4109a746/12OmNyKJiir",
"parentPublication": {
"id": "proceedings/icpr/2010/4109/0",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2011/4607/1/4607a106",
"title": "Splitting and Merging Gaussian Mixture Model Components: An Evolutionary Approach",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2011/4607a106/12OmNzahc3L",
"parentPublication": {
"id": "proceedings/icmla/2011/4607/1",
"title": "Machine Learning and Applications, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iita/2009/3859/2/3859b506",
"title": "A Greedy Merge Learning Algorithm for Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/iita/2009/3859b506/12OmNzd7bsE",
"parentPublication": {
"id": "proceedings/iita/2009/3859/2",
"title": "2009 Third International Symposium on Intelligent Information Technology Application",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2017/11/07938761",
"title": "A Fully-Pipelined Hardware Design for Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tc/2017/11/07938761/13rRUxjQyoA",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2019/02/08125179",
"title": "Constructing Pathway-Based Priors within a Gaussian Mixture Model for Bayesian Regression and Classification",
"doi": null,
"abstractUrl": "/journal/tb/2019/02/08125179/13rRUxlgyag",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2020/02/08462790",
"title": "A Gaussian Mixture-Model Exploiting Pathway Knowledge for Dissecting Cancer Heterogeneity",
"doi": null,
"abstractUrl": "/journal/tb/2020/02/08462790/13w3lphXmIE",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ithings-greencom-cpscom-smartdata/2018/7975/0/08726734",
"title": "A Finite Multi-Dimensional Generalized Gamma Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/ithings-greencom-cpscom-smartdata/2018/08726734/1axfoS4brAQ",
"parentPublication": {
"id": "proceedings/ithings-greencom-cpscom-smartdata/2018/7975/0",
"title": "2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyYm2vP",
"title": "Advances in Pattern Recognition, International Conference on",
"acronym": "icapr",
"groupId": "1002627",
"volume": "0",
"displayVolume": "0",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzTppDx",
"doi": "10.1109/ICAPR.2009.92",
"title": "Model Based Clustering of Audio Clips Using Gaussian Mixture Models",
"normalizedTitle": "Model Based Clustering of Audio Clips Using Gaussian Mixture Models",
"abstract": "The task of clustering multi-variate trajectory data of varying length exists in various domains. Model-based methods are capable of handling varying length trajectories without changing the length or structure. Hidden Markov models (HMMs) are widely used for trajectory data modeling. However, HMMs are not suitable for trajectories of long duration. In this paper, we propose a similarity based representation for multi-variate, varying length trajectories of long duration using Gaussian mixture models. Each trajectory is modeled by a Gaussian mixture model (GMM). The log-likelihood of a trajectory for a given GMM model is used as a similarity score. The scores corresponding to all the trajectories in the given data set and all the GMMs are used to form a score matrix that is used in a clustering algorithm. The proposed model based clustering method is applied on the audio clips which are multi-variate trajectories of varying length and long duration. The performance of the proposed method is much better than the method that uses a fixed length representation for an audio clip based on the perceptual features.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The task of clustering multi-variate trajectory data of varying length exists in various domains. Model-based methods are capable of handling varying length trajectories without changing the length or structure. Hidden Markov models (HMMs) are widely used for trajectory data modeling. However, HMMs are not suitable for trajectories of long duration. In this paper, we propose a similarity based representation for multi-variate, varying length trajectories of long duration using Gaussian mixture models. Each trajectory is modeled by a Gaussian mixture model (GMM). The log-likelihood of a trajectory for a given GMM model is used as a similarity score. The scores corresponding to all the trajectories in the given data set and all the GMMs are used to form a score matrix that is used in a clustering algorithm. The proposed model based clustering method is applied on the audio clips which are multi-variate trajectories of varying length and long duration. The performance of the proposed method is much better than the method that uses a fixed length representation for an audio clip based on the perceptual features.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The task of clustering multi-variate trajectory data of varying length exists in various domains. Model-based methods are capable of handling varying length trajectories without changing the length or structure. Hidden Markov models (HMMs) are widely used for trajectory data modeling. However, HMMs are not suitable for trajectories of long duration. In this paper, we propose a similarity based representation for multi-variate, varying length trajectories of long duration using Gaussian mixture models. Each trajectory is modeled by a Gaussian mixture model (GMM). The log-likelihood of a trajectory for a given GMM model is used as a similarity score. The scores corresponding to all the trajectories in the given data set and all the GMMs are used to form a score matrix that is used in a clustering algorithm. The proposed model based clustering method is applied on the audio clips which are multi-variate trajectories of varying length and long duration. The performance of the proposed method is much better than the method that uses a fixed length representation for an audio clip based on the perceptual features.",
"fno": "3520a047",
"keywords": [
"Model Based Clustering",
"Trajectory Clustering",
"Audio Clip Clustering",
"Gaussian Mixture Models"
],
"authors": [
{
"affiliation": null,
"fullName": "S. Chandrakala",
"givenName": "S.",
"surname": "Chandrakala",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "C. Chandra Sekhar",
"givenName": "C. Chandra",
"surname": "Sekhar",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icapr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-02-01T00:00:00",
"pubType": "proceedings",
"pages": "47-50",
"year": "2009",
"issn": null,
"isbn": "978-0-7695-3520-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3520a043",
"articleId": "12OmNqGA519",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3520a053",
"articleId": "12OmNCeK2di",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cw/2016/2303/0/2303a155",
"title": "Hybrid Recommender System Using Semi-supervised Clustering Based on Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2016/2303a155/12OmNBtCCFh",
"parentPublication": {
"id": "proceedings/cw/2016/2303/0",
"title": "2016 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmip/2017/5954/0/5954a113",
"title": "Statistical Analysis of Massive AIS Trajectories Using Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icmip/2017/5954a113/12OmNqAU6ED",
"parentPublication": {
"id": "proceedings/icmip/2017/5954/0",
"title": "2017 2nd International Conference on Multimedia and Image Processing (ICMIP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2012/4875/0/4875a421",
"title": "Using Wavelets and Gaussian Mixture Models for Audio Classification",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2012/4875a421/12OmNwtWfOr",
"parentPublication": {
"id": "proceedings/ism/2012/4875/0",
"title": "2012 IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2010/4109/0/4109a637",
"title": "CDP Mixture Models for Data Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2010/4109a637/12OmNynJMY8",
"parentPublication": {
"id": "proceedings/icpr/2010/4109/0",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2011/4607/1/4607a106",
"title": "Splitting and Merging Gaussian Mixture Model Components: An Evolutionary Approach",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2011/4607a106/12OmNzahc3L",
"parentPublication": {
"id": "proceedings/icmla/2011/4607/1",
"title": "Machine Learning and Applications, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/biotechno/2008/3191/0/3191a094",
"title": "sBGMM: A Stratified Beta-Gaussian Mixture Model for Clustering Genes with Multiple Data Sources",
"doi": null,
"abstractUrl": "/proceedings-article/biotechno/2008/3191a094/12OmNzcPA7r",
"parentPublication": {
"id": "proceedings/biotechno/2008/3191/0",
"title": "International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2013/05/ttp2013051051",
"title": "An Incremental DPMM-Based Method for Trajectory Clustering, Modeling, and Retrieval",
"doi": null,
"abstractUrl": "/journal/tp/2013/05/ttp2013051051/13rRUILtJAX",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2011/09/ttk2011091406",
"title": "Laplacian Regularized Gaussian Mixture Model for Data Clustering",
"doi": null,
"abstractUrl": "/journal/tk/2011/09/ttk2011091406/13rRUxBa5xB",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300g439",
"title": "Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300g439/1hVlkCHpXPi",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNx5GU2h",
"title": "2009 Third International Symposium on Intelligent Information Technology Application",
"acronym": "iita",
"groupId": "1002566",
"volume": "2",
"displayVolume": "2",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzd7bsE",
"doi": "10.1109/IITA.2009.273",
"title": "A Greedy Merge Learning Algorithm for Gaussian Mixture Model",
"normalizedTitle": "A Greedy Merge Learning Algorithm for Gaussian Mixture Model",
"abstract": "Gaussian mixture model (GMM) has been widely used in fields of image processing and investment data mining. However, in many practical applications, the number of the components is not known. This paper proposes a kind of greedy merge EM (GMEM) learning algorithm such that the number of Gaussians can be determined automatically with the minimum message length (MML) criterion. Moreover, the greedy merge learning algorithm is successfully applied to unsupervised data analysis. It is demonstrated well by the experiments that the proposed greedy merge EM (GMEM) learning algorithm can make both parameter learning and decide the number of the Gaussian mixture.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Gaussian mixture model (GMM) has been widely used in fields of image processing and investment data mining. However, in many practical applications, the number of the components is not known. This paper proposes a kind of greedy merge EM (GMEM) learning algorithm such that the number of Gaussians can be determined automatically with the minimum message length (MML) criterion. Moreover, the greedy merge learning algorithm is successfully applied to unsupervised data analysis. It is demonstrated well by the experiments that the proposed greedy merge EM (GMEM) learning algorithm can make both parameter learning and decide the number of the Gaussian mixture.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Gaussian mixture model (GMM) has been widely used in fields of image processing and investment data mining. However, in many practical applications, the number of the components is not known. This paper proposes a kind of greedy merge EM (GMEM) learning algorithm such that the number of Gaussians can be determined automatically with the minimum message length (MML) criterion. Moreover, the greedy merge learning algorithm is successfully applied to unsupervised data analysis. It is demonstrated well by the experiments that the proposed greedy merge EM (GMEM) learning algorithm can make both parameter learning and decide the number of the Gaussian mixture.",
"fno": "3859b506",
"keywords": [
"Gaussian Mixture Model",
"EM Algorithm",
"Model Selection",
"Merge Operation",
"Parameters Estimation"
],
"authors": [
{
"affiliation": null,
"fullName": "Yan Li",
"givenName": "Yan",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Lei Li",
"givenName": "Lei",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iita",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-11-01T00:00:00",
"pubType": "proceedings",
"pages": "506-509",
"year": "2009",
"issn": null,
"isbn": "978-0-7695-3859-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3859b503",
"articleId": "12OmNzIUfJ6",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3859b510",
"articleId": "12OmNvRU0mZ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icnc/2009/3736/6/3736f479",
"title": "A Novel Split and Merge EM Algorithm for Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2009/3736f479/12OmNAWH9FQ",
"parentPublication": {
"id": "proceedings/icnc/2009/3736/6",
"title": "2009 Fifth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2010/4083/0/4083a220",
"title": "Polony Identification Using the EM Algorithm Based on a Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2010/4083a220/12OmNCdBDXq",
"parentPublication": {
"id": "proceedings/bibe/2010/4083/0",
"title": "2010 IEEE International Conference on Bioinformatics and Bioengineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icig/2004/2244/0/01410503",
"title": "Greedy EM algorithm for robust t-mixture modeling",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2004/01410503/12OmNqBbHIJ",
"parentPublication": {
"id": "proceedings/icig/2004/2244/0",
"title": "Proceedings. Third International Conference on Image and Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aici/2009/3816/1/3816a434",
"title": "SAR Image Segmentation Based on Immune Genetic Algorithm and Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/aici/2009/3816a434/12OmNx7XH1q",
"parentPublication": {
"id": "proceedings/aici/2009/3816/1",
"title": "2009 International Conference on Artificial Intelligence and Computational Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisp/2008/3119/5/3119e542",
"title": "The Rao Detection of Weak Signal in Gaussian Mixture Noise",
"doi": null,
"abstractUrl": "/proceedings-article/cisp/2008/3119e542/12OmNylsZzR",
"parentPublication": {
"id": "proceedings/cisp/2008/3119/5",
"title": "International Congress on Image and Signal Processing (CISP 2008)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2011/4607/1/4607a106",
"title": "Splitting and Merging Gaussian Mixture Model Components: An Evolutionary Approach",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2011/4607a106/12OmNzahc3L",
"parentPublication": {
"id": "proceedings/icmla/2011/4607/1",
"title": "Machine Learning and Applications, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/biotechno/2008/3191/0/3191a094",
"title": "sBGMM: A Stratified Beta-Gaussian Mixture Model for Clustering Genes with Multiple Data Sources",
"doi": null,
"abstractUrl": "/proceedings-article/biotechno/2008/3191a094/12OmNzcPA7r",
"parentPublication": {
"id": "proceedings/biotechno/2008/3191/0",
"title": "International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000d427",
"title": "Sliced Wasserstein Distance for Learning Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000d427/17D45XwUAI2",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1cMGueDF0ti",
"title": "2019 16th Conference on Computer and Robot Vision (CRV)",
"acronym": "crv",
"groupId": "1001794",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1cMGuFJMJna",
"doi": "10.1109/CRV.2019.00012",
"title": "Direct Fitting of Gaussian Mixture Models",
"normalizedTitle": "Direct Fitting of Gaussian Mixture Models",
"abstract": "When fitting Gaussian Mixture Models to 3D geometry, the model is typically fit to point clouds, even when the shapes were obtained as 3D meshes. Here we present a formulation for fitting Gaussian Mixture Models (GMMs) directly to geometric objects, using the triangles of triangular mesh instead of using points sampled from its surface. We demonstrate that this modification enables fitting higher-quality GMMs under a wider range of initialization conditions. Additionally, models obtained from this fitting method are shown to produce an improvement in 3D registration for both meshes and RGB-D frames.",
"abstracts": [
{
"abstractType": "Regular",
"content": "When fitting Gaussian Mixture Models to 3D geometry, the model is typically fit to point clouds, even when the shapes were obtained as 3D meshes. Here we present a formulation for fitting Gaussian Mixture Models (GMMs) directly to geometric objects, using the triangles of triangular mesh instead of using points sampled from its surface. We demonstrate that this modification enables fitting higher-quality GMMs under a wider range of initialization conditions. Additionally, models obtained from this fitting method are shown to produce an improvement in 3D registration for both meshes and RGB-D frames.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "When fitting Gaussian Mixture Models to 3D geometry, the model is typically fit to point clouds, even when the shapes were obtained as 3D meshes. Here we present a formulation for fitting Gaussian Mixture Models (GMMs) directly to geometric objects, using the triangles of triangular mesh instead of using points sampled from its surface. We demonstrate that this modification enables fitting higher-quality GMMs under a wider range of initialization conditions. Additionally, models obtained from this fitting method are shown to produce an improvement in 3D registration for both meshes and RGB-D frames.",
"fno": "183800a025",
"keywords": [
"Approximation Theory",
"Gaussian Processes",
"Image Colour Analysis",
"Image Registration",
"Mesh Generation",
"Mixture Models",
"Stereo Image Processing",
"Direct Fitting",
"Gaussian Mixture Models",
"RGB D Frames",
"3 D Registration",
"Higher Quality GM Ms",
"Triangular Mesh",
"3 D Meshes",
"3 D Geometry",
"Three Dimensional Displays",
"Gaussian Mixture Model",
"Mathematical Model",
"Solid Modeling",
"Visualization",
"Robots",
"Gmm Shape Mesh Registration Approximation Representation 3 D Point Cloud Vision Mixture Model Slam"
],
"authors": [
{
"affiliation": "Carnegie Mellon University",
"fullName": "Leonid Keselman",
"givenName": "Leonid",
"surname": "Keselman",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University",
"fullName": "Martial Hebert",
"givenName": "Martial",
"surname": "Hebert",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "crv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-05-01T00:00:00",
"pubType": "proceedings",
"pages": "25-32",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-1838-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "183800a017",
"articleId": "1cMGuhkQK5i",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "183800a033",
"articleId": "1cMGurwZqKY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdm/2016/5473/0/07838000",
"title": "Gaussian Component Based Index for GMMs",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2016/07838000/12OmNAlvHTi",
"parentPublication": {
"id": "proceedings/icdm/2016/5473/0",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2012/4747/0/4747a246",
"title": "Searching Uncertain Data Represented by Non-axis Parallel Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2012/4747a246/12OmNBEGYKH",
"parentPublication": {
"id": "proceedings/icde/2012/4747/0",
"title": "2012 IEEE 28th International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icinis/2009/3852/0/3852a323",
"title": "Player Detection Algorithm Based on Gaussian Mixture Models Background Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/icinis/2009/3852a323/12OmNCd2rFh",
"parentPublication": {
"id": "proceedings/icinis/2009/3852/0",
"title": "Intelligent Networks and Intelligent Systems, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icesssymposia/2008/3288/0/3288a441",
"title": "Frequency and Space Domain Features for Image Classification Using Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/icesssymposia/2008/3288a441/12OmNrkjVhj",
"parentPublication": {
"id": "proceedings/icesssymposia/2008/3288/0",
"title": "Embedded Software and Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csse/2008/3336/2/3336c923",
"title": "Adaptive Gaussian Mixture Models Based Facial Actions Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/csse/2008/3336c923/12OmNvqW6XQ",
"parentPublication": {
"id": "proceedings/csse/2008/3336/6",
"title": "Computer Science and Software Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2017/3581/0/3581a704",
"title": "A Comparison Between Different Gaussian-Based Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2017/3581a704/12OmNwLOYWp",
"parentPublication": {
"id": "proceedings/aiccsa/2017/3581/0",
"title": "2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mediacom/2010/4136/0/4136a090",
"title": "An Improved Foreground Object Detection Method Based on Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/mediacom/2010/4136a090/12OmNzd7bE0",
"parentPublication": {
"id": "proceedings/mediacom/2010/4136/0",
"title": "2010 International Conference on Multimedia Communications (Mediacom 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2011/09/ttk2011091406",
"title": "Laplacian Regularized Gaussian Mixture Model for Data Clustering",
"doi": null,
"abstractUrl": "/journal/tk/2011/09/ttk2011091406/13rRUxBa5xB",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2017/11/07938761",
"title": "A Fully-Pipelined Hardware Design for Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tc/2017/11/07938761/13rRUxjQyoA",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903677",
"title": "GRay: Ray Casting for Visualization and Interactive Data Exploration of Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903677/1GZoj8mhSPS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1iTvczdcyc0",
"title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"acronym": "cvprw",
"groupId": "8972688",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1iTvhS5ckIo",
"doi": "10.1109/CVPRW.2019.00153",
"title": "Parametric Skeleton Generation via Gaussian Mixture Models",
"normalizedTitle": "Parametric Skeleton Generation via Gaussian Mixture Models",
"abstract": "We propose an efficient and effective control point extraction algorithm for parametric skeleton generation. The object skeleton pixels are predicted via an hourglass network and partitioned into skeleton branches using Gaussian Mixture Models. For each skeleton branch, a Bezier curve is utilized to generate the control points. The radius of the skeleton is computed by the distance between the border of the object and the Bezier curve. The branches are sorted by the area so that the parametric skeleton representation is unique. For the Parametric SkelNetOn competition, the proposed approach achieves the prediction score of 11793.89, which is in the first place on the performance leader-board.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose an efficient and effective control point extraction algorithm for parametric skeleton generation. The object skeleton pixels are predicted via an hourglass network and partitioned into skeleton branches using Gaussian Mixture Models. For each skeleton branch, a Bezier curve is utilized to generate the control points. The radius of the skeleton is computed by the distance between the border of the object and the Bezier curve. The branches are sorted by the area so that the parametric skeleton representation is unique. For the Parametric SkelNetOn competition, the proposed approach achieves the prediction score of 11793.89, which is in the first place on the performance leader-board.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose an efficient and effective control point extraction algorithm for parametric skeleton generation. The object skeleton pixels are predicted via an hourglass network and partitioned into skeleton branches using Gaussian Mixture Models. For each skeleton branch, a Bezier curve is utilized to generate the control points. The radius of the skeleton is computed by the distance between the border of the object and the Bezier curve. The branches are sorted by the area so that the parametric skeleton representation is unique. For the Parametric SkelNetOn competition, the proposed approach achieves the prediction score of 11793.89, which is in the first place on the performance leader-board.",
"fno": "250600b167",
"keywords": [
"Computational Geometry",
"Gaussian Processes",
"Image Representation",
"Image Thinning",
"Mixture Models",
"Parametric Skeleton Generation",
"Gaussian Mixture Models",
"Efficient Control Point Extraction Algorithm",
"Effective Control Point Extraction Algorithm",
"Object Skeleton Pixels",
"Skeleton Branch",
"Bezier Curve",
"Control Points",
"Parametric Skeleton Representation",
"Parametric Skel Net On Competition",
"Skeleton",
"Shape",
"Sorting",
"Training",
"Prediction Algorithms",
"Conferences",
"Gaussian Mixture Model"
],
"authors": [
{
"affiliation": "University of Chinese Academy of Sciences, China",
"fullName": "Chang Liu",
"givenName": "Chang",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chinese Academy of Sciences, China; Institute of Information Engineering, China",
"fullName": "Dezhao Luo",
"givenName": "Dezhao",
"surname": "Luo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chinese Academy of Sciences, China; Institute of Information Engineering, China",
"fullName": "Yifei Zhang",
"givenName": "Yifei",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University, United States",
"fullName": "Wei Ke",
"givenName": "Wei",
"surname": "Ke",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chinese Academy of Sciences, China",
"fullName": "Fang Wan",
"givenName": "Fang",
"surname": "Wan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Chinese Academy of Sciences, China",
"fullName": "Qixiang Ye",
"givenName": "Qixiang",
"surname": "Ye",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvprw",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-06-01T00:00:00",
"pubType": "proceedings",
"pages": "1167-1171",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-2506-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "250600b162",
"articleId": "1iTve7OMlRm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "250600b172",
"articleId": "1iTvcZW3aqA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2012/2216/0/06460530",
"title": "Single image super-resolution using Gaussian Mixture Model",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460530/12OmNCctfn2",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/u-media/2011/4493/0/4493a168",
"title": "3D Skeleton Construction by Multi-view 2D Images and 3D Model Segmentation",
"doi": null,
"abstractUrl": "/proceedings-article/u-media/2011/4493a168/12OmNs0TKKE",
"parentPublication": {
"id": "proceedings/u-media/2011/4493/0",
"title": "International Conference on Ubi-Media Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccet/2009/3521/1/3521a326",
"title": "3D Mesh Skeleton Extraction Based on Feature Points",
"doi": null,
"abstractUrl": "/proceedings-article/iccet/2009/3521a326/12OmNvAAtk8",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2017/3581/0/3581a704",
"title": "A Comparison Between Different Gaussian-Based Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2017/3581a704/12OmNwLOYWp",
"parentPublication": {
"id": "proceedings/aiccsa/2017/3581/0",
"title": "2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2011/4409/0/4409a286",
"title": "Parametric Characterization of Multimodal Distributions with Non-gaussian Modes",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2011/4409a286/12OmNwl8GID",
"parentPublication": {
"id": "proceedings/icdmw/2011/4409/0",
"title": "2011 IEEE 11th International Conference on Data Mining Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209c269",
"title": "Pruning the 3D Curve Skeleton",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209c269/12OmNzICEBg",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2007/03/i0449",
"title": "Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution",
"doi": null,
"abstractUrl": "/journal/tp/2007/03/i0449/13rRUxDqS57",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000d427",
"title": "Sliced Wasserstein Distance for Learning Gaussian Mixture Models",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000d427/17D45XwUAI2",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/12/09122436",
"title": "Towards Automatic Skeleton Extraction With Skeleton Grafting",
"doi": null,
"abstractUrl": "/journal/tg/2021/12/09122436/1kRRC5VRVMQ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100c136",
"title": "Distance and Edge Transform for Skeleton Extraction",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100c136/1yNi3UnSipG",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyFCvPf",
"title": "Parallel and Large-Data Visualization and Graphics, IEEE Symposium on",
"acronym": "pvg",
"groupId": "1002140",
"volume": "0",
"displayVolume": "0",
"year": "2003",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBsue7j",
"doi": "10.1109/PVGS.2003.1249046",
"title": "Distributed Interactive Ray Tracing for Large Volume Visualization",
"normalizedTitle": "Distributed Interactive Ray Tracing for Large Volume Visualization",
"abstract": "We have constructed a distributed parallel ray tracing system that interactively produces isosurface renderings from large data sets on a cluster of commodity PCs. The program was derived from the SCI Institute's interactive ray tracer (*-Ray), which utilizes small to large shared memory platforms, such as the SGI Origin series, to interact with very large-scale data sets. Making this approach work efficiently on a cluster requires attention to numerous system-level issues, especially when rendering data sets larger than the address space of each cluster node. The rendering engine is an image parallel ray tracer with a supervisor/workers organization. Each node in the cluster runs a multi-threaded application. A minimal abstraction layer on top of TCP links the nodes, and enables asynchronous message handling. For large volumes, render threads obtain data bricks on demand from an object-based software distributed shared memory. Caching improves performance by reducing the amount of data transfers for a reasonable working set size. For large data sets, the cluster-based interactive ray tracer performs comparably with an SGI Origin system. We examine the parameter space of the renderer and provide experimental results for interactive rendering of large (7.5 GB) data sets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We have constructed a distributed parallel ray tracing system that interactively produces isosurface renderings from large data sets on a cluster of commodity PCs. The program was derived from the SCI Institute's interactive ray tracer (*-Ray), which utilizes small to large shared memory platforms, such as the SGI Origin series, to interact with very large-scale data sets. Making this approach work efficiently on a cluster requires attention to numerous system-level issues, especially when rendering data sets larger than the address space of each cluster node. The rendering engine is an image parallel ray tracer with a supervisor/workers organization. Each node in the cluster runs a multi-threaded application. A minimal abstraction layer on top of TCP links the nodes, and enables asynchronous message handling. For large volumes, render threads obtain data bricks on demand from an object-based software distributed shared memory. Caching improves performance by reducing the amount of data transfers for a reasonable working set size. For large data sets, the cluster-based interactive ray tracer performs comparably with an SGI Origin system. We examine the parameter space of the renderer and provide experimental results for interactive rendering of large (7.5 GB) data sets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We have constructed a distributed parallel ray tracing system that interactively produces isosurface renderings from large data sets on a cluster of commodity PCs. The program was derived from the SCI Institute's interactive ray tracer (*-Ray), which utilizes small to large shared memory platforms, such as the SGI Origin series, to interact with very large-scale data sets. Making this approach work efficiently on a cluster requires attention to numerous system-level issues, especially when rendering data sets larger than the address space of each cluster node. The rendering engine is an image parallel ray tracer with a supervisor/workers organization. Each node in the cluster runs a multi-threaded application. A minimal abstraction layer on top of TCP links the nodes, and enables asynchronous message handling. For large volumes, render threads obtain data bricks on demand from an object-based software distributed shared memory. Caching improves performance by reducing the amount of data transfers for a reasonable working set size. For large data sets, the cluster-based interactive ray tracer performs comparably with an SGI Origin system. We examine the parameter space of the renderer and provide experimental results for interactive rendering of large (7.5 GB) data sets.",
"fno": "20910012",
"keywords": [
"Visualization",
"Interactive Ray Tracing",
"Large Data"
],
"authors": [
{
"affiliation": "The University of Utah",
"fullName": "David E DeMarle",
"givenName": "David E",
"surname": "DeMarle",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Utah",
"fullName": "Steven Parker",
"givenName": "Steven",
"surname": "Parker",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Utah",
"fullName": "Mark Hartner",
"givenName": "Mark",
"surname": "Hartner",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Utah",
"fullName": "Christiaan Gribble",
"givenName": "Christiaan",
"surname": "Gribble",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Utah",
"fullName": "Charles Hansen",
"givenName": "Charles",
"surname": "Hansen",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "pvg",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2003-10-01T00:00:00",
"pubType": "proceedings",
"pages": "12",
"year": "2003",
"issn": null,
"isbn": "0-7695-2091-X",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "20910011",
"articleId": "12OmNBO3KjK",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "20910013",
"articleId": "12OmNvAAtys",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/pvg/2003/2091/0/20910011",
"title": "Distributed Interactive Ray Tracing of Dynamic Scenes",
"doi": null,
"abstractUrl": "/proceedings-article/pvg/2003/20910011/12OmNBO3KjK",
"parentPublication": {
"id": "proceedings/pvg/2003/2091/0",
"title": "Parallel and Large-Data Visualization and Graphics, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2008/2741/0/04634635",
"title": "Interactive SIMD ray tracing for large deformable tetrahedral meshes",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634635/12OmNBV9IdJ",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2008/2741/0/04634637",
"title": "Ray tracing with the BSP tree",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634637/12OmNvpw7dh",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2006/0693/0/04061561",
"title": "Design for Parallel Interactive Ray Tracing Systems",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2006/04061561/12OmNwFidcU",
"parentPublication": {
"id": "proceedings/rt/2006/0693/0",
"title": "IEEE Symposium on Interactive Ray Tracing 2006",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2008/2741/0/04634619",
"title": "Large ray packets for real-time Whitted ray tracing",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634619/12OmNwcCITG",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccd/2010/8936/0/05647555",
"title": "Efficient MIMD architectures for high-performance ray tracing",
"doi": null,
"abstractUrl": "/proceedings-article/iccd/2010/05647555/12OmNx8OuAD",
"parentPublication": {
"id": "proceedings/iccd/2010/8936/0",
"title": "2010 IEEE International Conference on Computer Design",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcc-euc/2013/5088/0/06831966",
"title": "Large Scale Satellite Imagery Simulations with Physically Based Ray Tracing on Tianhe-1A Supercomputer",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-euc/2013/06831966/12OmNxUdv6S",
"parentPublication": {
"id": "proceedings/hpcc-euc/2013/5088/0",
"title": "2013 IEEE International Conference on High Performance Computing and Communications (HPCC) & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (EUC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pvgs/2003/8122/0/01249046",
"title": "Distributed interactive ray tracing for large volume visualization",
"doi": null,
"abstractUrl": "/proceedings-article/pvgs/2003/01249046/12OmNz2TCDv",
"parentPublication": {
"id": "proceedings/pvgs/2003/8122/0",
"title": "IEEE Symposium on Parallel and Large-Data Visualization and Graphics 2003",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/1999/03/v0238",
"title": "Interactive Ray Tracing for Volume Visualization",
"doi": null,
"abstractUrl": "/journal/tg/1999/03/v0238/13rRUxOdD85",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ldav/2018/6873/0/08739241",
"title": "Galaxy: Asynchronous Ray Tracing for Large High-Fidelity Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/ldav/2018/08739241/1b1xcjia3Be",
"parentPublication": {
"id": "proceedings/ldav/2018/6873/0",
"title": "2018 IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNs4S8ww",
"title": "IEEE/ EG Symposium on Interactive Ray Tracing 2007",
"acronym": "rt",
"groupId": "1001330",
"volume": "0",
"displayVolume": "0",
"year": "2007",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqJZgLN",
"doi": "10.1109/RT.2007.4342598",
"title": "Realtime Ray Tracing on GPU with BVH-based Packet Traversal",
"normalizedTitle": "Realtime Ray Tracing on GPU with BVH-based Packet Traversal",
"abstract": "Recent GPU ray tracers can already achieve performance competitive to that of their CPU counterparts. Nevertheless, these systems can not yet fully exploit the capabilities of modern GPUs and can only handle medium-sized, static scenes. In this paper we present a BVH-based GPU ray tracer with a parallel packet traversal algorithm using a shared stack. We also present a fast, CPU-based BVH construction algorithm which very accurately approximates the surface area heuristic using streamed binning while still being one order of magnitude faster than previously published results. Furthermore, using a BVH allows us to push the size limit of supported scenes on the GPU: We can now ray trace the 12.7 million triangle Power Plant at 1024 times 1024 image resolution with 3 fps, including shading and shadows.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recent GPU ray tracers can already achieve performance competitive to that of their CPU counterparts. Nevertheless, these systems can not yet fully exploit the capabilities of modern GPUs and can only handle medium-sized, static scenes. In this paper we present a BVH-based GPU ray tracer with a parallel packet traversal algorithm using a shared stack. We also present a fast, CPU-based BVH construction algorithm which very accurately approximates the surface area heuristic using streamed binning while still being one order of magnitude faster than previously published results. Furthermore, using a BVH allows us to push the size limit of supported scenes on the GPU: We can now ray trace the 12.7 million triangle Power Plant at 1024 times 1024 image resolution with 3 fps, including shading and shadows.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recent GPU ray tracers can already achieve performance competitive to that of their CPU counterparts. Nevertheless, these systems can not yet fully exploit the capabilities of modern GPUs and can only handle medium-sized, static scenes. In this paper we present a BVH-based GPU ray tracer with a parallel packet traversal algorithm using a shared stack. We also present a fast, CPU-based BVH construction algorithm which very accurately approximates the surface area heuristic using streamed binning while still being one order of magnitude faster than previously published results. Furthermore, using a BVH allows us to push the size limit of supported scenes on the GPU: We can now ray trace the 12.7 million triangle Power Plant at 1024 times 1024 image resolution with 3 fps, including shading and shadows.",
"fno": "04342598",
"keywords": [
"Ray Tracing",
"Parallel Packet Traversal",
"GPU Ray Tracers",
"BVH Based Packet Traversal",
"Realtime Ray Tracing",
"Ray Tracing",
"Layout",
"Computer Graphics",
"Yarn",
"Acceleration",
"Data Structures",
"Random Access Memory",
"Furnaces",
"Light Sources",
"Streaming Media",
"I 3 6 Computer Graphics Methodology And Techniques Realism Graphics Data Structures And Data Types I 3 7 Computer Graphics Three Dimensional Graphics And Realism Raytracing"
],
"authors": [
{
"affiliation": "MPI Informatik, e-mail: guenther@mpi-inf.mpg.de",
"fullName": "Johannes Gunther",
"givenName": "Johannes",
"surname": "Gunther",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Saarland University, e-mail: popov@graphics.cs.uni-sb.de",
"fullName": "Stefan Popov",
"givenName": "Stefan",
"surname": "Popov",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "MPI Informatik, e-mail: hpseidel@mpi-inf.mpg.de",
"fullName": "Hans-Peter Seidel",
"givenName": "Hans-Peter",
"surname": "Seidel",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Saarland University, e-mail: slusallek@graphics.cs.uni-sb.de",
"fullName": "Philipp Slusallek",
"givenName": "Philipp",
"surname": "Slusallek",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "rt",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2007-09-01T00:00:00",
"pubType": "proceedings",
"pages": "113-118",
"year": "2007",
"issn": null,
"isbn": "978-1-4244-1629-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "04342582",
"articleId": "12OmNx57HKA",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "04342599",
"articleId": "12OmNy5hRnZ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/rt/2008/2741/0/04634641",
"title": "A straightforward CUDA implementation for interactive ray-tracing",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634641/12OmNAY79ml",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sbac-pad/2009/3857/0/3857a041",
"title": "kD-Tree Traversal Implementations for Ray Tracing on Massive Multiprocessors: A Comparative Study",
"doi": null,
"abstractUrl": "/proceedings-article/sbac-pad/2009/3857a041/12OmNvJXeAz",
"parentPublication": {
"id": "proceedings/sbac-pad/2009/3857/0",
"title": "Computer Architecture and High Performance Computing, Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2008/2741/0/04634637",
"title": "Ray tracing with the BSP tree",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634637/12OmNvpw7dh",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2006/0693/0/04061544",
"title": "RT-DEFORM: Interactive Ray Tracing of Dynamic Scenes using BVHs",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2006/04061544/12OmNwErpUk",
"parentPublication": {
"id": "proceedings/rt/2006/0693/0",
"title": "IEEE Symposium on Interactive Ray Tracing 2006",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sccc/2010/4400/0/4400a011",
"title": "Improving the Performance of a Ray Tracing Algorithm Using a GPU",
"doi": null,
"abstractUrl": "/proceedings-article/sccc/2010/4400a011/12OmNx0RJ0z",
"parentPublication": {
"id": "proceedings/sccc/2010/4400/0",
"title": "2010 XXIX International Conference of the Chilean Computer Science Society",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cadgraphics/2011/4497/0/4497a087",
"title": "SIMD Friendly Ray Tracing on GPU",
"doi": null,
"abstractUrl": "/proceedings-article/cadgraphics/2011/4497a087/12OmNxFaLiE",
"parentPublication": {
"id": "proceedings/cadgraphics/2011/4497/0",
"title": "Computer-Aided Design and Computer Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2008/2741/0/04634640",
"title": "Augenblick: A user-friendly and extensible realtime ray tracing architecture",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634640/12OmNyvY9rf",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rt/2008/2741/0/04634633",
"title": "Adaptive ray packet reordering",
"doi": null,
"abstractUrl": "/proceedings-article/rt/2008/04634633/12OmNzvhvB6",
"parentPublication": {
"id": "proceedings/rt/2008/2741/0",
"title": "Symposium on Interactive Ray Tracing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2015/03/06960897",
"title": "HART: A Hybrid Architecture for Ray Tracing Animated Scenes",
"doi": null,
"abstractUrl": "/journal/tg/2015/03/06960897/13rRUNvgyWp",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cecit/2021/3757/0/375700b168",
"title": "Stackless KD-Tree Traversal For Ray Tracing",
"doi": null,
"abstractUrl": "/proceedings-article/cecit/2021/375700b168/1CdEOBZgTVC",
"parentPublication": {
"id": "proceedings/cecit/2021/3757/0",
"title": "2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzUPpvV",
"title": "Scientific and Statistical Database Management, International Conference on",
"acronym": "ssdbm",
"groupId": "1000645",
"volume": "0",
"displayVolume": "0",
"year": "1996",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAkniYx",
"doi": "10.1109/SSDM.1996.505913",
"title": "Statistical Dependencies",
"normalizedTitle": "Statistical Dependencies",
"abstract": "In a database where numeric data has been obtained by inaccurate methods (measurements, calculations involving error propagation) it is unlikely to have equal stored values for a single, repeatedly measured/calculated value. As a result, instances which should satisfy but actually \"nearly\" satisfy a functional dependency cannot be decomposed. For such cases, we introduce the notion of statistical dependency (sd) as an extension of functional dependencies (fds). We show how the well-known axioms for fds can be used in the case of sds; decompositions w.r.t. sds are also presented. The resulting decomposition can be used to answer statistical queries. Finally, we study a possible way of generalizing the multivalued dependencies in the same manner.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In a database where numeric data has been obtained by inaccurate methods (measurements, calculations involving error propagation) it is unlikely to have equal stored values for a single, repeatedly measured/calculated value. As a result, instances which should satisfy but actually \"nearly\" satisfy a functional dependency cannot be decomposed. For such cases, we introduce the notion of statistical dependency (sd) as an extension of functional dependencies (fds). We show how the well-known axioms for fds can be used in the case of sds; decompositions w.r.t. sds are also presented. The resulting decomposition can be used to answer statistical queries. Finally, we study a possible way of generalizing the multivalued dependencies in the same manner.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In a database where numeric data has been obtained by inaccurate methods (measurements, calculations involving error propagation) it is unlikely to have equal stored values for a single, repeatedly measured/calculated value. As a result, instances which should satisfy but actually \"nearly\" satisfy a functional dependency cannot be decomposed. For such cases, we introduce the notion of statistical dependency (sd) as an extension of functional dependencies (fds). We show how the well-known axioms for fds can be used in the case of sds; decompositions w.r.t. sds are also presented. The resulting decomposition can be used to answer statistical queries. Finally, we study a possible way of generalizing the multivalued dependencies in the same manner.",
"fno": "72640032",
"keywords": [
"Statistical Dependencies",
"Relational Model"
],
"authors": [
{
"affiliation": "A.I.Cuza University, OMANIA",
"fullName": "Paul Cotofrei",
"givenName": "Paul",
"surname": "Cotofrei",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "A.I.Cuza University, OMANIA",
"fullName": "Henri Luchian",
"givenName": "Henri",
"surname": "Luchian",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ssdbm",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1996-06-01T00:00:00",
"pubType": "proceedings",
"pages": "32",
"year": "1996",
"issn": null,
"isbn": "0-8186-7264-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "72640022",
"articleId": "12OmNCfAPMx",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "72640044",
"articleId": "12OmNySosM1",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxH9X7v",
"title": "Parallel and Distributed Systems, International Conference on",
"acronym": "icpads",
"groupId": "1000534",
"volume": "0",
"displayVolume": "0",
"year": "2000",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAlvHSJ",
"doi": "10.1109/ICPADS.2000.857739",
"title": "Parallel Spatial Joins Using Grid Files",
"normalizedTitle": "Parallel Spatial Joins Using Grid Files",
"abstract": "The most costly spatial operation in spatial databases is a spatial join, which combines objects from two data sets based on spatial predicates. Even if the execution time of sequential processing of a spatial join has been considerably improved over the last few years, the response time is far from meeting the requirements of interactive users. In this paper, we have developed two kinds of parallel spatial join algorithms based on grid files: a parallel spatial join using a multi-assignment grid file and a parallel spatial join using a single-assignment grid file. We also present the cost of the two join algorithms in terms of the number of MBR comparisons. The experimental tests on the MIMD parallel machine with shared disks show that the first join algorithm based on disjoint decomposition of a data space outperforms the second based on non-disjoint decomposition.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The most costly spatial operation in spatial databases is a spatial join, which combines objects from two data sets based on spatial predicates. Even if the execution time of sequential processing of a spatial join has been considerably improved over the last few years, the response time is far from meeting the requirements of interactive users. In this paper, we have developed two kinds of parallel spatial join algorithms based on grid files: a parallel spatial join using a multi-assignment grid file and a parallel spatial join using a single-assignment grid file. We also present the cost of the two join algorithms in terms of the number of MBR comparisons. The experimental tests on the MIMD parallel machine with shared disks show that the first join algorithm based on disjoint decomposition of a data space outperforms the second based on non-disjoint decomposition.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The most costly spatial operation in spatial databases is a spatial join, which combines objects from two data sets based on spatial predicates. Even if the execution time of sequential processing of a spatial join has been considerably improved over the last few years, the response time is far from meeting the requirements of interactive users. In this paper, we have developed two kinds of parallel spatial join algorithms based on grid files: a parallel spatial join using a multi-assignment grid file and a parallel spatial join using a single-assignment grid file. We also present the cost of the two join algorithms in terms of the number of MBR comparisons. The experimental tests on the MIMD parallel machine with shared disks show that the first join algorithm based on disjoint decomposition of a data space outperforms the second based on non-disjoint decomposition.",
"fno": "05680531",
"keywords": [
"Spatial Database",
"Spatial Join",
"Parallel Processing"
],
"authors": [
{
"affiliation": "Pusan Info-Tech College",
"fullName": "Jin-Deog Kim",
"givenName": "Jin-Deog",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Pusan National University",
"fullName": "Bong-Hee Hong",
"givenName": "Bong-Hee",
"surname": "Hong",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icpads",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2000-07-01T00:00:00",
"pubType": "proceedings",
"pages": "531",
"year": "2000",
"issn": null,
"isbn": "0-7695-0571-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05680523",
"articleId": "12OmNvAiSis",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05680537",
"articleId": "12OmNzXFoFx",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzcxZpZ",
"title": "Semantic Computing and Systems, IEEE International Workshop on",
"acronym": "wscs",
"groupId": "1002008",
"volume": "0",
"displayVolume": "0",
"year": "2008",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAlvHZ6",
"doi": "10.1109/WSCS.2008.15",
"title": "Automatic Acquisition of Semantic Elements Based on Statistical Decomposition",
"normalizedTitle": "Automatic Acquisition of Semantic Elements Based on Statistical Decomposition",
"abstract": "The implement of machine translation system based on semantic element (SE) requires a large scale semantic element base. An automatic acquisition method for SEs based on statistical decomposition was proposed in this paper. Firstly, .analogical decomposition was applied to decompose abandonable SE and two conditions are found to assure the correctness of decomposition. Secondly, three statistics were designed, namely parameter index, translation index and language model index, to measure the rationality of analogical decomposition. Finally, multi-attribute decision making values for the above three statistics were prioritized to choose the best decomposition. Abandonable SE could be decomposed iteratively thereafter. Experimental results show that the accuracy has reached around 60%.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The implement of machine translation system based on semantic element (SE) requires a large scale semantic element base. An automatic acquisition method for SEs based on statistical decomposition was proposed in this paper. Firstly, .analogical decomposition was applied to decompose abandonable SE and two conditions are found to assure the correctness of decomposition. Secondly, three statistics were designed, namely parameter index, translation index and language model index, to measure the rationality of analogical decomposition. Finally, multi-attribute decision making values for the above three statistics were prioritized to choose the best decomposition. Abandonable SE could be decomposed iteratively thereafter. Experimental results show that the accuracy has reached around 60%.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The implement of machine translation system based on semantic element (SE) requires a large scale semantic element base. An automatic acquisition method for SEs based on statistical decomposition was proposed in this paper. Firstly, .analogical decomposition was applied to decompose abandonable SE and two conditions are found to assure the correctness of decomposition. Secondly, three statistics were designed, namely parameter index, translation index and language model index, to measure the rationality of analogical decomposition. Finally, multi-attribute decision making values for the above three statistics were prioritized to choose the best decomposition. Abandonable SE could be decomposed iteratively thereafter. Experimental results show that the accuracy has reached around 60%.",
"fno": "3316a076",
"keywords": [
"Machine Translation",
"Semantic Element",
"Automatic Acquisition",
"Statistical Decomposition"
],
"authors": [
{
"affiliation": null,
"fullName": "Miao Fang",
"givenName": "Miao",
"surname": "Fang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Qi Zhao",
"givenName": "Qi",
"surname": "Zhao",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wscs",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2008-07-01T00:00:00",
"pubType": "proceedings",
"pages": "76-81",
"year": "2008",
"issn": null,
"isbn": "978-0-7695-3316-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3316a072",
"articleId": "12OmNwIHopB",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3316a082",
"articleId": "12OmNCgrCYf",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/esiat/2009/3682/3/3682c583",
"title": "An Automatic Translation Evaluation System Based on Semantic Similarities and Fuzzy Neartude",
"doi": null,
"abstractUrl": "/proceedings-article/esiat/2009/3682c583/12OmNBKmXp4",
"parentPublication": {
"id": "proceedings/esiat/2009/3682/3",
"title": "Environmental Science and Information Application Technology, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/async/1996/7298/0/72980048",
"title": "General Conditions for the Decomposition of State-Holding Elements",
"doi": null,
"abstractUrl": "/proceedings-article/async/1996/72980048/12OmNqHItDp",
"parentPublication": {
"id": "proceedings/async/1996/7298/0",
"title": "Proceedings Second International Symposium on Advanced Research in Asynchronous Circuits and Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2000/0909/0/09090326",
"title": "Interactive generalization of a translation example using queries based on a semantic hierarchy",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2000/09090326/12OmNvB9Fzm",
"parentPublication": {
"id": "proceedings/ictai/2000/0909/0",
"title": "Proceedings 12th IEEE Internationals Conference on Tools with Artificial Intelligence. ICTAI 2000",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aici/2010/4225/1/4225a429",
"title": "Study on Curve Phenomenon between English and Chinese and its Solution",
"doi": null,
"abstractUrl": "/proceedings-article/aici/2010/4225a429/12OmNx8OumT",
"parentPublication": {
"id": "proceedings/aici/2010/4225/1",
"title": "Artificial Intelligence and Computational Intelligence, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/socpar/2009/3879/0/3879a283",
"title": "Image Semantic Extraction Using Latent Semantic Indexing on Image Retrieval Automatic-Annotation",
"doi": null,
"abstractUrl": "/proceedings-article/socpar/2009/3879a283/12OmNy2agXa",
"parentPublication": {
"id": "proceedings/socpar/2009/3879/0",
"title": "Soft Computing and Pattern Recognition, International Conference of",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2011/0063/0/06130408",
"title": "A multi-affine model for tensor decomposition",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2011/06130408/12OmNzBwGvJ",
"parentPublication": {
"id": "proceedings/iccvw/2011/0063/0",
"title": "2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2004/04/x4067",
"title": "Dynamic Invocation of Semantic Web Services That Use Unfamiliar Ontologies",
"doi": null,
"abstractUrl": "/magazine/ex/2004/04/x4067/13rRUx0xPAK",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1995/01/i0002",
"title": "Decomposition of Arbitrarily Shaped Morphological Structuring Elements",
"doi": null,
"abstractUrl": "/journal/tp/1995/01/i0002/13rRUxBa5yj",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1990/01/i0038",
"title": "Morphological Shape Decomposition",
"doi": null,
"abstractUrl": "/journal/tp/1990/01/i0038/13rRUygT7nT",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1998/02/i0217",
"title": "Decomposition of Arbitrarily Shaped Binary Morphological Structuring Elements Using Genetic Algorithms",
"doi": null,
"abstractUrl": "/journal/tp/1998/02/i0217/13rRUynHuk7",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNz4BdvM",
"title": "2011 Fourth International Conference on Information and Computing (ICIC)",
"acronym": "icic",
"groupId": "1002818",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBNM94s",
"doi": "10.1109/ICIC.2011.135",
"title": "The Spatial Statistical Analysis of Regional Economy in Jiangsu Province",
"normalizedTitle": "The Spatial Statistical Analysis of Regional Economy in Jiangsu Province",
"abstract": "In this paper we discuss the differences of development level of regional economy in Jiangsu province by means of spatial statistical methods. The empirical results show that the development of regional economy in Jiangsu province presents spatial agglomeration. The spatial characteristic of region can't be ignored while studying disparity of regional economy.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper we discuss the differences of development level of regional economy in Jiangsu province by means of spatial statistical methods. The empirical results show that the development of regional economy in Jiangsu province presents spatial agglomeration. The spatial characteristic of region can't be ignored while studying disparity of regional economy.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper we discuss the differences of development level of regional economy in Jiangsu province by means of spatial statistical methods. The empirical results show that the development of regional economy in Jiangsu province presents spatial agglomeration. The spatial characteristic of region can't be ignored while studying disparity of regional economy.",
"fno": "05954626",
"keywords": [
"Economics",
"Statistical Analysis",
"Spatial Statistical Analysis",
"Regional Economy",
"Jiangsu Province",
"Spatial Agglomeration",
"Correlation",
"Cities And Towns",
"Statistical Analysis",
"Economic Indicators",
"Analytical Models",
"Spatial Databases",
"Spatial Statistical Analysis",
"Morans I",
"Spatial Autocorrelation",
"Regional Economy"
],
"authors": [
{
"affiliation": null,
"fullName": "Qin Weiliang",
"givenName": "Qin",
"surname": "Weiliang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Shi Wenjun",
"givenName": "Shi",
"surname": "Wenjun",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Xu Ying",
"givenName": "Xu",
"surname": "Ying",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icic",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2011-04-01T00:00:00",
"pubType": "proceedings",
"pages": "545-547",
"year": "2011",
"issn": "2160-7443",
"isbn": "978-1-61284-688-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05954625",
"articleId": "12OmNBkP3AB",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05954627",
"articleId": "12OmNvonIGM",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccis/2013/5004/0/5004a660",
"title": "Estimate the Impact of Human Capital on Regional Labor Productivity in Jiangsu Province",
"doi": null,
"abstractUrl": "/proceedings-article/iccis/2013/5004a660/12OmNA0dMFo",
"parentPublication": {
"id": "proceedings/iccis/2013/5004/0",
"title": "2013 International Conference on Computational and Information Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccis/2013/5004/0/5004a656",
"title": "Econometrics Forecasting the Marine Economic Development in Jiangsu Province",
"doi": null,
"abstractUrl": "/proceedings-article/iccis/2013/5004a656/12OmNAKuoVD",
"parentPublication": {
"id": "proceedings/iccis/2013/5004/0",
"title": "2013 International Conference on Computational and Information Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2008/3357/2/3357c701",
"title": "Study on Regional Highway Macroscopic Logistics Hinge City Layout Based on Principal Component Analysis and Dynamic Clustering - Taking Jiangsu Province for Example",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2008/3357c701/12OmNAS9zpO",
"parentPublication": {
"id": "icicta/2008/3357/2",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciii/2011/4523/1/4523a585",
"title": "The Value-added Effect of Educational Value Chain: An Empirical Study of Jiangsu Province",
"doi": null,
"abstractUrl": "/proceedings-article/iciii/2011/4523a585/12OmNrAMEYu",
"parentPublication": {
"id": "proceedings/iciii/2011/4523/1",
"title": "International Conference on Information Management, Innovation Management and Industrial Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmecg/2014/6543/0/6543a280",
"title": "The Influence of Regional Intellectual Capital on Regional Economic Development: Evidence from Shandong Province",
"doi": null,
"abstractUrl": "/proceedings-article/icmecg/2014/6543a280/12OmNwCsdyI",
"parentPublication": {
"id": "proceedings/icmecg/2014/6543/0",
"title": "2014 International Conference on Management of e-Commerce and e-Government (ICMeCG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isdea/2015/9393/0/9393a494",
"title": "Local Goverment Debt Risk Early Warning Algortithm Based on Fuzzy Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/isdea/2015/9393a494/12OmNwNwzHT",
"parentPublication": {
"id": "proceedings/isdea/2015/9393/0",
"title": "2015 Sixth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icrmem/2008/3402/0/3402a159",
"title": "Comprehensive Evaluation of Energy Saving Social Construction of Jiangsu Province",
"doi": null,
"abstractUrl": "/proceedings-article/icrmem/2008/3402a159/12OmNxG1yFS",
"parentPublication": {
"id": "proceedings/icrmem/2008/3402/0",
"title": "2008 International Conference on Risk Management & Engineering Management",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icise/2009/3887/0/pid978032",
"title": "An Empirical Analysis on the Asymmetric Regional Effects of Chinese Monetary Policy: Based on the VAR Models of Jiangsu and Henan Province",
"doi": null,
"abstractUrl": "/proceedings-article/icise/2009/pid978032/12OmNy2rRWY",
"parentPublication": {
"id": "proceedings/icise/2009/3887/0",
"title": "Information Science and Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2015/7644/0/7644a412",
"title": "Empirical Study on the Effect of Jiangsu Province on Logistics FDI in Opening Situation",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2015/7644a412/12OmNy5R3Gq",
"parentPublication": {
"id": "proceedings/icicta/2015/7644/0",
"title": "2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccis/2010/4270/0/4270b224",
"title": "Analyzing Economic Spatial-Temporal Disparities at County Level in Jiangsu Based on ESDA-GIS",
"doi": null,
"abstractUrl": "/proceedings-article/iccis/2010/4270b224/12OmNzaQodD",
"parentPublication": {
"id": "proceedings/iccis/2010/4270/0",
"title": "2010 International Conference on Computational and Information Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzDvSo0",
"title": "SC14: International Conference for High Performance Computing, Networking, Storage and Analysis",
"acronym": "sc",
"groupId": "1000729",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBaBuSz",
"doi": "10.1109/SC.2014.86",
"title": "High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation",
"normalizedTitle": "High-Performance Computation of Distributed-Memory Parallel 3D Voronoi and Delaunay Tessellation",
"abstract": "Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization, but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbor points need to be exchanged among the sub domains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization, but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbor points need to be exchanged among the sub domains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization, but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbor points need to be exchanged among the sub domains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.",
"fno": "5500a997",
"keywords": [
"Libraries",
"Parallel Algorithms",
"Computational Geometry",
"Three Dimensional Displays",
"Face",
"Data Models",
"Heuristic Algorithms",
"Delaunay Tessellation",
"Computational Geometry",
"Voronoi"
],
"authors": [
{
"affiliation": null,
"fullName": "Tom Peterka",
"givenName": "Tom",
"surname": "Peterka",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Dmitriy Morozov",
"givenName": "Dmitriy",
"surname": "Morozov",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Carolyn Phillips",
"givenName": "Carolyn",
"surname": "Phillips",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "sc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-11-01T00:00:00",
"pubType": "proceedings",
"pages": "997-1007",
"year": "2014",
"issn": "2167-4337",
"isbn": "978-1-4799-5500-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "5500a982",
"articleId": "12OmNx965GB",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "5500b008",
"articleId": "12OmNzXFoId",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/smi/2008/2260/0/04547934",
"title": "Computation and properties of Centroidal Voronoi Tessellation",
"doi": null,
"abstractUrl": "/proceedings-article/smi/2008/04547934/12OmNAKuoTH",
"parentPublication": {
"id": "proceedings/smi/2008/2260/0",
"title": "IEEE International Conference on Shape Modeling and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2012/1910/0/06257663",
"title": "Decomposition of a Protein Solution into Voronoi Shells and Delaunay Layers",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2012/06257663/12OmNrEL2Dz",
"parentPublication": {
"id": "proceedings/isvd/2012/1910/0",
"title": "2012 Ninth International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cadgraphics/2011/4497/0/4497a494",
"title": "Delaunay/Voronoi Dual Representation of Smooth 2-Manifolds",
"doi": null,
"abstractUrl": "/proceedings-article/cadgraphics/2011/4497a494/12OmNs5rkQF",
"parentPublication": {
"id": "proceedings/cadgraphics/2011/4497/0",
"title": "Computer-Aided Design and Computer Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2011/4483/0/4483a177",
"title": "Computing 2D Periodic Centroidal Voronoi Tessellation",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2011/4483a177/12OmNwHhoTy",
"parentPublication": {
"id": "proceedings/isvd/2011/4483/0",
"title": "2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2012/1910/0/06257653",
"title": "Localizing the Delaunay Triangulation and its Parallel Implementation",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2012/06257653/12OmNwoxSe8",
"parentPublication": {
"id": "proceedings/isvd/2012/1910/0",
"title": "2012 Ninth International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/1988/0862/0/00196249",
"title": "Image representation using Voronoi tessellation: adaptive and secure",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/1988/00196249/12OmNx5Yv7Q",
"parentPublication": {
"id": "proceedings/cvpr/1988/0862/0",
"title": "Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2012/1910/0/06257669",
"title": "On the Construction of a Generalized Voronoi Inverse of a Rectangular Tessellation",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2012/06257669/12OmNxGAKVI",
"parentPublication": {
"id": "proceedings/isvd/2012/1910/0",
"title": "2012 Ninth International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2012/1910/0/06257659",
"title": "Rigidity of Ball-polyhedra via Truncated Voronoi and Delaunay Complexes",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2012/06257659/12OmNyuyadO",
"parentPublication": {
"id": "proceedings/isvd/2012/1910/0",
"title": "2012 Ninth International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1983/01/04767353",
"title": "Segmenting Dot Patterns by Voronoi Diagram Concavity",
"doi": null,
"abstractUrl": "/journal/tp/1983/01/04767353/13rRUNvgzjc",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2006/2630/0/04124796",
"title": "Voronoi and Delaunay Tilings for Lattices",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2006/04124796/17D45WGGoMi",
"parentPublication": {
"id": "proceedings/isvd/2006/2630/0",
"title": "2006 3rd International Symposium on Voronoi Diagrams in Science and Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNy5hRcm",
"title": "Database Applications in Non-Traditional Environments, International Symposium on",
"acronym": "dante",
"groupId": "1002388",
"volume": "0",
"displayVolume": "0",
"year": "1999",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNs5rl2w",
"doi": "10.1109/DANTE.1999.844964",
"title": "Parallel Spatial Join Algorithms Using Grid Files",
"normalizedTitle": "Parallel Spatial Join Algorithms Using Grid Files",
"abstract": "The most costly spatial operation in spatial databases is a spatial join, which combines objects from two data sets based on spatial predicates such as, intersects or contains. Even if the execution time of sequential spatial join processing has considerably been improved over the last few years, the response time is far from meeting the requirements of interactive users.In this paper, we have designed two kinds of parallel spatial join algorithms based on grid files: a parallel spatial join using a multi-assignment grid file and a parallel spatial join using a single-assignment grid file. Three kinds of methods of task allocation for improving their performances: static, dynamic, semi-dynamic have been examined for determining which task allocation strategy based on grid files shows the best performance. The experimental tests have been conducted on the MIMD parallel machine; with shared disks conclude that the first join algorithm based on disjoint decomposition of data space outperforms the second based on non-disjoint decomposition. Also, the semi-dynamic task allocation method is the best.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The most costly spatial operation in spatial databases is a spatial join, which combines objects from two data sets based on spatial predicates such as, intersects or contains. Even if the execution time of sequential spatial join processing has considerably been improved over the last few years, the response time is far from meeting the requirements of interactive users.In this paper, we have designed two kinds of parallel spatial join algorithms based on grid files: a parallel spatial join using a multi-assignment grid file and a parallel spatial join using a single-assignment grid file. Three kinds of methods of task allocation for improving their performances: static, dynamic, semi-dynamic have been examined for determining which task allocation strategy based on grid files shows the best performance. The experimental tests have been conducted on the MIMD parallel machine; with shared disks conclude that the first join algorithm based on disjoint decomposition of data space outperforms the second based on non-disjoint decomposition. Also, the semi-dynamic task allocation method is the best.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The most costly spatial operation in spatial databases is a spatial join, which combines objects from two data sets based on spatial predicates such as, intersects or contains. Even if the execution time of sequential spatial join processing has considerably been improved over the last few years, the response time is far from meeting the requirements of interactive users.In this paper, we have designed two kinds of parallel spatial join algorithms based on grid files: a parallel spatial join using a multi-assignment grid file and a parallel spatial join using a single-assignment grid file. Three kinds of methods of task allocation for improving their performances: static, dynamic, semi-dynamic have been examined for determining which task allocation strategy based on grid files shows the best performance. The experimental tests have been conducted on the MIMD parallel machine; with shared disks conclude that the first join algorithm based on disjoint decomposition of data space outperforms the second based on non-disjoint decomposition. Also, the semi-dynamic task allocation method is the best.",
"fno": "04960226",
"keywords": [
"Spatial Database",
"Spatial Join",
"Parallel Processing"
],
"authors": [
{
"affiliation": "Pusan Info-Tech College",
"fullName": "Jin-Deog Kim",
"givenName": "Jin-Deog",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Pusan National University",
"fullName": "Bong-Hee Hong",
"givenName": "Bong-Hee",
"surname": "Hong",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dante",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1999-11-01T00:00:00",
"pubType": "proceedings",
"pages": "226",
"year": "1999",
"issn": null,
"isbn": "0-7695-0496-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "04960218",
"articleId": "12OmNCcKQGn",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "04960237",
"articleId": "12OmNBcAGNa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNCfAPCr",
"title": "4th International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2007)",
"acronym": "isvd",
"groupId": "1001201",
"volume": "0",
"displayVolume": "0",
"year": "2007",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzUxO6N",
"doi": "10.1109/ISVD.2007.16",
"title": "Detecting Stellar Streams in the Halos of Galaxies with Voronoi Tessellations",
"normalizedTitle": "Detecting Stellar Streams in the Halos of Galaxies with Voronoi Tessellations",
"abstract": "Galaxy formation models oriented towards a ACDM cosmology envision galaxies as being built through the accretion of dwarf galaxies. Such galaxy accretion should appear as tidally-disrupted streams of stars in the halo of the host galaxy. Yet these stellar streams have very low surface brightnesses, making their detection difficult. We propose that surface luminosity maps, derived from Hubble space telescope advanced camera for surveys resolved star photometry, can be used to reveal stellar structures in the halos of galaxies. To create surface luminosity maps with high, yet consistent, signal to noise, the centroidal Voronoi tessellation is used. The Voronoi tessellation offers the advantage of optimal binning to preserve spatial resolution. As preliminary testing has shown, the technique reveals halo structures, such as the dwarf galaxy near NGC 4631, as bright, compact, Voronoi regions.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Galaxy formation models oriented towards a ACDM cosmology envision galaxies as being built through the accretion of dwarf galaxies. Such galaxy accretion should appear as tidally-disrupted streams of stars in the halo of the host galaxy. Yet these stellar streams have very low surface brightnesses, making their detection difficult. We propose that surface luminosity maps, derived from Hubble space telescope advanced camera for surveys resolved star photometry, can be used to reveal stellar structures in the halos of galaxies. To create surface luminosity maps with high, yet consistent, signal to noise, the centroidal Voronoi tessellation is used. The Voronoi tessellation offers the advantage of optimal binning to preserve spatial resolution. As preliminary testing has shown, the technique reveals halo structures, such as the dwarf galaxy near NGC 4631, as bright, compact, Voronoi regions.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Galaxy formation models oriented towards a ACDM cosmology envision galaxies as being built through the accretion of dwarf galaxies. Such galaxy accretion should appear as tidally-disrupted streams of stars in the halo of the host galaxy. Yet these stellar streams have very low surface brightnesses, making their detection difficult. We propose that surface luminosity maps, derived from Hubble space telescope advanced camera for surveys resolved star photometry, can be used to reveal stellar structures in the halos of galaxies. To create surface luminosity maps with high, yet consistent, signal to noise, the centroidal Voronoi tessellation is used. The Voronoi tessellation offers the advantage of optimal binning to preserve spatial resolution. As preliminary testing has shown, the technique reveals halo structures, such as the dwarf galaxy near NGC 4631, as bright, compact, Voronoi regions.",
"fno": "28690300",
"keywords": [
"Astronomy Computing",
"Computational Geometry",
"Galaxies",
"Stellar Streams",
"Galaxy Formation Models",
"ACDM Cosmology",
"Dwarf Galaxies",
"Hubble Space Telescope",
"Star Photometry",
"Stellar Structures",
"Centroidal Voronoi Tessellation",
"Optimal Binning",
"Telescopes",
"Spatial Resolution",
"Cameras",
"Testing",
"Streaming Media",
"Visualization",
"Brightness",
"Signal Resolution",
"Photometry",
"Dark Energy"
],
"authors": [
{
"affiliation": "Rice University, USA",
"fullName": "Jonathan Sick",
"givenName": "Jonathan",
"surname": "Sick",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Space Telescope Science Institute, USA",
"fullName": "Roelof de Jong",
"givenName": "Roelof de",
"surname": "Jong",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "isvd",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2007-07-01T00:00:00",
"pubType": "proceedings",
"pages": "300-304",
"year": "2007",
"issn": null,
"isbn": "0-7695-2869-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "04276125",
"articleId": "12OmNAo45Cr",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "28690230",
"articleId": "12OmNz2TCEY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/isvd/2006/2630/0/26300112",
"title": "Clustering of 3D Spatial Points Using Maximum Likelihood Estimator over Voronoi Tessellations: Study of the Galaxy Distribution in Redshift Space",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2006/26300112/12OmNy6ZrZV",
"parentPublication": {
"id": "proceedings/isvd/2006/2630/0",
"title": "2006 3rd International Symposium on Voronoi Diagrams in Science and Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2007/2869/0/28690230",
"title": "Voronoi Tessellations and the Cosmic Web: Spatial Patterns and Clustering across the Universe",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2007/28690230/12OmNz2TCEY",
"parentPublication": {
"id": "proceedings/isvd/2007/2869/0",
"title": "4th International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2007)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2012/06/06186738",
"title": "VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations",
"doi": null,
"abstractUrl": "/journal/tp/2012/06/06186738/13rRUy0qnHC",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzayNEJ",
"title": "2017 Data Compression Conference (DCC)",
"acronym": "dcc",
"groupId": "1000177",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBghtsc",
"doi": "10.1109/DCC.2017.49",
"title": "Optimize Genomics Data Compression with Hardware Accelerator",
"normalizedTitle": "Optimize Genomics Data Compression with Hardware Accelerator",
"abstract": "Genomics is a Big Data science, the rate of increase in DNA sequencing is significantly exceeding the rate of increase in storage capacity, study shows the genomics data generation will exceed Twitter, YouTube, and astrophysics data combined by the year 2025. Storage and data management have become one of the most challenging bottlenecks in genomics and life sciences research. Data compression is an important technique to improve the efficiency of genomics data analysis and storage, and is widely deployed in the IT infrastructure in the life science institutes. In this paper we analyze the data compression characterization in the genomics workflows, and evaluate the performance & cost for different compression algorithms in the genomics analysis tool, we present a new hardware acceleration method that efficiently compresses DNA sequences with the reduced computation time and CPU utilization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Genomics is a Big Data science, the rate of increase in DNA sequencing is significantly exceeding the rate of increase in storage capacity, study shows the genomics data generation will exceed Twitter, YouTube, and astrophysics data combined by the year 2025. Storage and data management have become one of the most challenging bottlenecks in genomics and life sciences research. Data compression is an important technique to improve the efficiency of genomics data analysis and storage, and is widely deployed in the IT infrastructure in the life science institutes. In this paper we analyze the data compression characterization in the genomics workflows, and evaluate the performance & cost for different compression algorithms in the genomics analysis tool, we present a new hardware acceleration method that efficiently compresses DNA sequences with the reduced computation time and CPU utilization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Genomics is a Big Data science, the rate of increase in DNA sequencing is significantly exceeding the rate of increase in storage capacity, study shows the genomics data generation will exceed Twitter, YouTube, and astrophysics data combined by the year 2025. Storage and data management have become one of the most challenging bottlenecks in genomics and life sciences research. Data compression is an important technique to improve the efficiency of genomics data analysis and storage, and is widely deployed in the IT infrastructure in the life science institutes. In this paper we analyze the data compression characterization in the genomics workflows, and evaluate the performance & cost for different compression algorithms in the genomics analysis tool, we present a new hardware acceleration method that efficiently compresses DNA sequences with the reduced computation time and CPU utilization.",
"fno": "07923729",
"keywords": [
"Big Data",
"Biology Computing",
"Data Compression",
"DNA",
"Genomics",
"Microprocessor Chips",
"Molecular Biophysics",
"Social Networking Online",
"Storage Management",
"Genomic Data Compression Optimization",
"Hardware Accelerator",
"Big Data Science",
"DNA Sequencing",
"Storage Capacity",
"Genomics Data Generation",
"Twitter",
"You Tube",
"Astrophysics Data",
"Data Management",
"Storage Management",
"Data Compression",
"Life Science Institutes",
"Genomics Analysis Tool",
"DNA Sequence Compression",
"CPU Utilization",
"Genomics",
"Bioinformatics",
"Hardware",
"Sorting",
"Data Compression",
"Benchmark Testing",
"Software",
"Genomics",
"Compression",
"Accelerator",
"ZFS"
],
"authors": [
{
"affiliation": null,
"fullName": "Weigang Li",
"givenName": "Weigang",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dcc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-04-01T00:00:00",
"pubType": "proceedings",
"pages": "446-446",
"year": "2017",
"issn": "2375-0359",
"isbn": "978-1-5090-6721-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "07923728",
"articleId": "12OmNy4IEZn",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07923730",
"articleId": "12OmNz5JCh1",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iscc/2017/1629/0/08024547",
"title": "Big data analytics in genomics: The point on Deep Learning solutions",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2017/08024547/12OmNCcKQGd",
"parentPublication": {
"id": "proceedings/iscc/2017/1629/0",
"title": "2017 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ddecs/2010/6612/0/05491817",
"title": "Data compression in hardware — The Burrows-Wheeler approach",
"doi": null,
"abstractUrl": "/proceedings-article/ddecs/2010/05491817/12OmNvA1hnA",
"parentPublication": {
"id": "proceedings/ddecs/2010/6612/0",
"title": "13th IEEE Symposium on Design and Diagnostics of Electronic Circuits and Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217953",
"title": "Scalable data structure to compress next-generation sequencing files and its application to compressive genomics",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217953/12OmNvs4vnu",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2013/05/ttb2013051275",
"title": "FRESCO: Referential Compression of Highly Similar Sequences",
"doi": null,
"abstractUrl": "/journal/tb/2013/05/ttb2013051275/13rRUwI5U19",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2017/06/07470248",
"title": "Benchmark Dataset for Whole Genome Sequence Compression",
"doi": null,
"abstractUrl": "/journal/tb/2017/06/07470248/13rRUxASutX",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/01/09702707",
"title": "Guest Editorial: Deep Learning For Genomics",
"doi": null,
"abstractUrl": "/journal/tb/2022/01/09702707/1AH3dAEy5C8",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlsid/2019/0409/0/040900a347",
"title": "k-Core: Hardware Accelerator for k-Mer Generation and Counting used in Computational Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/vlsid/2019/040900a347/1a3wXDYtDfa",
"parentPublication": {
"id": "proceedings/vlsid/2019/0409/0",
"title": "2019 32nd International Conference on VLSI Design and 2019 18th International Conference on Embedded Systems (VLSID)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/05/08936480",
"title": "Lossy Compression of Quality Values in Sequencing Data",
"doi": null,
"abstractUrl": "/journal/tb/2021/05/08936480/1fRyZVsDrZC",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/drbsd-5/2019/6017/0/601700a028",
"title": "Exploring Lossy Compression of Gene Expression Matrices",
"doi": null,
"abstractUrl": "/proceedings-article/drbsd-5/2019/601700a028/1gAwQoS60Ao",
"parentPublication": {
"id": "proceedings/drbsd-5/2019/6017/0",
"title": "2019 IEEE/ACM 5th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-5)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpca/2021/2235/0/223500a399",
"title": "EXMA: A Genomics Accelerator for Exact-Matching",
"doi": null,
"abstractUrl": "/proceedings-article/hpca/2021/223500a399/1t0HX1C7Sso",
"parentPublication": {
"id": "proceedings/hpca/2021/2235/0",
"title": "2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNC1GueN",
"title": "2015 IEEE/ACM 1st International Workshop on Software Engineering for High Performance Computing in Science (SE4HPCS)",
"acronym": "se4hpcs",
"groupId": "1808864",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqIQSiQ",
"doi": "10.1109/SE4HPCS.2015.14",
"title": "Computation for Genomics Knowledge Discovery",
"normalizedTitle": "Computation for Genomics Knowledge Discovery",
"abstract": "Knowledge discovery in genomics involves large scale graph processing and inference which is different from high-performance computing in genomics for sequence analysis. Genomics datasets are becoming increasing large and varied due to advances in biotechnology. Traditional sequence analysis therefore is computation-intensive for tasks such as assembly of reads, mapping reads to genomes, variation analysis across genomes, sequence similarity, sequence clustering, phylogenetics, and sequence motif and pattern finding. Beyond these data analysis steps come annotation steps to determine genes and their roles. This is knowledge discovery by inference from experimentally characterized genes, with provenance tracking the evidence for and against the annotation, post-processing by rules to catch systematic errors in annotation, gap-filling in systems biology network models, and propagation of changes in our knowledge of experimentally characterized genes. How can we engineer software for these kinds of systems that require high performance computing?",
"abstracts": [
{
"abstractType": "Regular",
"content": "Knowledge discovery in genomics involves large scale graph processing and inference which is different from high-performance computing in genomics for sequence analysis. Genomics datasets are becoming increasing large and varied due to advances in biotechnology. Traditional sequence analysis therefore is computation-intensive for tasks such as assembly of reads, mapping reads to genomes, variation analysis across genomes, sequence similarity, sequence clustering, phylogenetics, and sequence motif and pattern finding. Beyond these data analysis steps come annotation steps to determine genes and their roles. This is knowledge discovery by inference from experimentally characterized genes, with provenance tracking the evidence for and against the annotation, post-processing by rules to catch systematic errors in annotation, gap-filling in systems biology network models, and propagation of changes in our knowledge of experimentally characterized genes. How can we engineer software for these kinds of systems that require high performance computing?",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Knowledge discovery in genomics involves large scale graph processing and inference which is different from high-performance computing in genomics for sequence analysis. Genomics datasets are becoming increasing large and varied due to advances in biotechnology. Traditional sequence analysis therefore is computation-intensive for tasks such as assembly of reads, mapping reads to genomes, variation analysis across genomes, sequence similarity, sequence clustering, phylogenetics, and sequence motif and pattern finding. Beyond these data analysis steps come annotation steps to determine genes and their roles. This is knowledge discovery by inference from experimentally characterized genes, with provenance tracking the evidence for and against the annotation, post-processing by rules to catch systematic errors in annotation, gap-filling in systems biology network models, and propagation of changes in our knowledge of experimentally characterized genes. How can we engineer software for these kinds of systems that require high performance computing?",
"fno": "7082a046",
"keywords": [
"Genomics",
"Bioinformatics",
"Organisms",
"Proteins",
"Ontologies",
"Databases",
"Provenance",
"Bioinformatics",
"Graph Processing",
"Change Propagation"
],
"authors": [
{
"affiliation": null,
"fullName": "Gregory Butler",
"givenName": "Gregory",
"surname": "Butler",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "se4hpcs",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-05-01T00:00:00",
"pubType": "proceedings",
"pages": "46-50",
"year": "2015",
"issn": null,
"isbn": "978-1-4673-7082-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "7082a038",
"articleId": "12OmNCctfas",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "7082a051",
"articleId": "12OmNyp9MgL",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/biovis/2012/4729/0/06378593",
"title": "Gene-RiViT: A visualization tool for comparative analysis of gene neighborhoods in prokaryotes",
"doi": null,
"abstractUrl": "/proceedings-article/biovis/2012/06378593/12OmNAQrYEK",
"parentPublication": {
"id": "proceedings/biovis/2012/4729/0",
"title": "2012 IEEE Symposium on Biological Data Visualization (BioVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dexa/2011/0982/0/06059857",
"title": "Crossing Isorthology and Microsynteny to Resolve Multigenic Families Functional Annotation",
"doi": null,
"abstractUrl": "/proceedings-article/dexa/2011/06059857/12OmNxXCGOK",
"parentPublication": {
"id": "proceedings/dexa/2011/0982/0",
"title": "2011 22nd International Workshop on Database and Expert Systems Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2007/1509/0/04375743",
"title": "GPX: A Tool for the Exploration and Visualization of Genome Evolution",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2007/04375743/12OmNy4IEVO",
"parentPublication": {
"id": "proceedings/bibe/2007/1509/0",
"title": "7th IEEE International Conference on Bioinformatics and Bioengineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2014/05/06817586",
"title": "Genome-Wide Protein Function Prediction through Multi-Instance Multi-Label Learning",
"doi": null,
"abstractUrl": "/journal/tb/2014/05/06817586/13rRUy0HYPJ",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bdcat/2018/5502/0/550200a041",
"title": "ntPack: A Software Package for Big Data in Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/bdcat/2018/550200a041/17D45XDIXRG",
"parentPublication": {
"id": "proceedings/bdcat/2018/5502/0",
"title": "2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2018/8161/0/08633632",
"title": "Business Management System for Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2018/08633632/17D45XwUAKG",
"parentPublication": {
"id": "proceedings/iisa/2018/8161/0",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/02/09184986",
"title": "Functional Genomics Platform, A Cloud-Based Platform for Studying Microbial Life at Scale",
"doi": null,
"abstractUrl": "/journal/tb/2022/02/09184986/1mNmLZioXLO",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09312982",
"title": "Predictive Analytics on Genomic Data with High-Performance Computing",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09312982/1qmgcZ9hW2Q",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313323",
"title": "A Review of Artificial Intelligence Applications in Bacterial Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313323/1qmghh3sqFW",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/06/09477014",
"title": "Heuristics for Genome Rearrangement Distance With Replicated Genes",
"doi": null,
"abstractUrl": "/journal/tb/2021/06/09477014/1v2LYKjTPgs",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNz5JC3w",
"title": "2014 IEEE International Conference on Big Data (Big Data)",
"acronym": "big-data",
"groupId": "1802964",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNxH9XfX",
"doi": "10.1109/BigData.2014.7004392",
"title": "Big data in genomics: An overview",
"normalizedTitle": "Big data in genomics: An overview",
"abstract": "Studies show that healthcare industry in U.S. alone could save billions of dollars by utilizing big data and analytics technologies. Big Data can improve operational efficiencies, help predict and plan responses to disease epidemics, improve the quality of monitoring of clinical trials, and optimize healthcare spending at all levels from patients to hospital systems to governments. Another key area is genomics sequencing which is expected to be the future of healthcare. In this paper the authors look at the opportunities, work in progress and challenges of genomics with emerging big data and analytics.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Studies show that healthcare industry in U.S. alone could save billions of dollars by utilizing big data and analytics technologies. Big Data can improve operational efficiencies, help predict and plan responses to disease epidemics, improve the quality of monitoring of clinical trials, and optimize healthcare spending at all levels from patients to hospital systems to governments. Another key area is genomics sequencing which is expected to be the future of healthcare. In this paper the authors look at the opportunities, work in progress and challenges of genomics with emerging big data and analytics.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Studies show that healthcare industry in U.S. alone could save billions of dollars by utilizing big data and analytics technologies. Big Data can improve operational efficiencies, help predict and plan responses to disease epidemics, improve the quality of monitoring of clinical trials, and optimize healthcare spending at all levels from patients to hospital systems to governments. Another key area is genomics sequencing which is expected to be the future of healthcare. In this paper the authors look at the opportunities, work in progress and challenges of genomics with emerging big data and analytics.",
"fno": "07004392",
"keywords": [
"Bioinformatics",
"Genomics",
"Big Data",
"Sequential Analysis",
"DNA",
"Diseases",
"Genomics",
"Big Data",
"Healthcare"
],
"authors": [
{
"affiliation": "Cisco Systems, Inc./University of Southern California, San Jose, CA 95134, USA",
"fullName": "Ruchie Bhardwaj",
"givenName": "Ruchie",
"surname": "Bhardwaj",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cisco Systems, Inc., Herndon, VA 20171, USA",
"fullName": "Adhiraaj Sethi",
"givenName": "Adhiraaj",
"surname": "Sethi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cisco Systems, Inc., San Jose, CA 95134, USA",
"fullName": "Raghunath Nambiar",
"givenName": "Raghunath",
"surname": "Nambiar",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "big-data",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-10-01T00:00:00",
"pubType": "proceedings",
"pages": "45-49",
"year": "2014",
"issn": null,
"isbn": "978-1-4799-5666-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "07004391",
"articleId": "12OmNxwENiv",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07004393",
"articleId": "12OmNyOq4Sc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/big-data/2015/9926/0/07364117",
"title": "Big Data: Cloud computing in genomics applications",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2015/07364117/12OmNAWpyp4",
"parentPublication": {
"id": "proceedings/big-data/2015/9926/0",
"title": "2015 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icws/2017/0752/0/0752a237",
"title": "An Experimental Study of a Biosequence Big Data Analysis Service",
"doi": null,
"abstractUrl": "/proceedings-article/icws/2017/0752a237/12OmNBOlltd",
"parentPublication": {
"id": "proceedings/icws/2017/0752/0",
"title": "2017 IEEE International Conference on Web Services (ICWS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2017/1629/0/08024547",
"title": "Big data analytics in genomics: The point on Deep Learning solutions",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2017/08024547/12OmNCcKQGd",
"parentPublication": {
"id": "proceedings/iscc/2017/1629/0",
"title": "2017 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2021/02/08290833",
"title": "A Deep Learning-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets",
"doi": null,
"abstractUrl": "/journal/bd/2021/02/08290833/13rRUNvyan3",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bdcat/2018/5502/0/550200a041",
"title": "ntPack: A Software Package for Big Data in Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/bdcat/2018/550200a041/17D45XDIXRG",
"parentPublication": {
"id": "proceedings/bdcat/2018/5502/0",
"title": "2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2018/8161/0/08633685",
"title": "Smart Laboratory Information System Accelerates Genomics Research",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2018/08633685/17D45Xq6dzO",
"parentPublication": {
"id": "proceedings/iisa/2018/8161/0",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2018/8161/0/08633632",
"title": "Business Management System for Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2018/08633632/17D45XwUAKG",
"parentPublication": {
"id": "proceedings/iisa/2018/8161/0",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/01/09702707",
"title": "Guest Editorial: Deep Learning For Genomics",
"doi": null,
"abstractUrl": "/journal/tb/2022/01/09702707/1AH3dAEy5C8",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccsa/2019/2847/0/284700a102",
"title": "Personalized Nutrition Solution Based on Nutrigenomics",
"doi": null,
"abstractUrl": "/proceedings-article/iccsa/2019/284700a102/1dPoPw53CH6",
"parentPublication": {
"id": "proceedings/iccsa/2019/2847/0",
"title": "2019 19th International Conference on Computational Science and Its Applications (ICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2019/2999/0/08969697",
"title": "optimizing the Research of DNA Sequences in a NoSQL Document Database: A Preliminary Study",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2019/08969697/1h0K3Yby48w",
"parentPublication": {
"id": "proceedings/iscc/2019/2999/0",
"title": "2019 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKisI",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"acronym": "iisa",
"groupId": "1802852",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45Xq6dzO",
"doi": "10.1109/IISA.2018.8633685",
"title": "Smart Laboratory Information System Accelerates Genomics Research",
"normalizedTitle": "Smart Laboratory Information System Accelerates Genomics Research",
"abstract": "Genomics is now commonly accepted to support the implementation of precision medicine, and some of techniques such as human whole genome sequencing, human whole exome sequencing, and cancer genomics, have been used to more accurately guide individual clinical diagnosis. For the foreseeable future, clinical diagnosis will broadly use genomics. Therefore, the acceleration of the sequencing and analysis work-flows is very important, especially for clinical emergency treatment. The experimental work-flow includes sample warehousing, plasma separation, nucleic acid extraction, library construction, concentration and peak map detection, pooling, sequencing, and etc. In this paper, we introduce a smart laboratory information system that helps laboratories to acquire samples efficiently, track samples, automate routine tasks, optimize procedures and workflows, operate tens of thousands of samples in parallel, as well as integrate with sequencing instruments and analysis pipelines. The system could accelerate a lot the production work-flow of genomics research laboratories.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Genomics is now commonly accepted to support the implementation of precision medicine, and some of techniques such as human whole genome sequencing, human whole exome sequencing, and cancer genomics, have been used to more accurately guide individual clinical diagnosis. For the foreseeable future, clinical diagnosis will broadly use genomics. Therefore, the acceleration of the sequencing and analysis work-flows is very important, especially for clinical emergency treatment. The experimental work-flow includes sample warehousing, plasma separation, nucleic acid extraction, library construction, concentration and peak map detection, pooling, sequencing, and etc. In this paper, we introduce a smart laboratory information system that helps laboratories to acquire samples efficiently, track samples, automate routine tasks, optimize procedures and workflows, operate tens of thousands of samples in parallel, as well as integrate with sequencing instruments and analysis pipelines. The system could accelerate a lot the production work-flow of genomics research laboratories.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Genomics is now commonly accepted to support the implementation of precision medicine, and some of techniques such as human whole genome sequencing, human whole exome sequencing, and cancer genomics, have been used to more accurately guide individual clinical diagnosis. For the foreseeable future, clinical diagnosis will broadly use genomics. Therefore, the acceleration of the sequencing and analysis work-flows is very important, especially for clinical emergency treatment. The experimental work-flow includes sample warehousing, plasma separation, nucleic acid extraction, library construction, concentration and peak map detection, pooling, sequencing, and etc. In this paper, we introduce a smart laboratory information system that helps laboratories to acquire samples efficiently, track samples, automate routine tasks, optimize procedures and workflows, operate tens of thousands of samples in parallel, as well as integrate with sequencing instruments and analysis pipelines. The system could accelerate a lot the production work-flow of genomics research laboratories.",
"fno": "08633685",
"keywords": [
"Sequential Analysis",
"Bioinformatics",
"Genomics",
"Instruments",
"DNA",
"Business",
"Information Systems"
],
"authors": [
{
"affiliation": "Beijing Language and Culture University, School of Information Science, Beijing, 100083, China",
"fullName": "Jitao Yang",
"givenName": "Jitao",
"surname": "Yang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iisa",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-07-01T00:00:00",
"pubType": "proceedings",
"pages": "1-4",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-8161-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08633668",
"articleId": "17D45VtKiuO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08633675",
"articleId": "17D45Xh13sJ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iscc/2017/1629/0/08024547",
"title": "Big data analytics in genomics: The point on Deep Learning solutions",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2017/08024547/12OmNCcKQGd",
"parentPublication": {
"id": "proceedings/iscc/2017/1629/0",
"title": "2017 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2016/0679/0/07543751",
"title": "New trends in Biotechnology: The point on NGS Cloud computing solutions",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2016/07543751/12OmNqC2v16",
"parentPublication": {
"id": "proceedings/iscc/2016/0679/0",
"title": "2016 IEEE Symposium on Computers and Communication (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2014/5666/0/07004392",
"title": "Big data in genomics: An overview",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2014/07004392/12OmNxH9XfX",
"parentPublication": {
"id": "proceedings/big-data/2014/5666/0",
"title": "2014 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2017/06/07501834",
"title": "A Survey of Software and Hardware Approaches to Performing Read Alignment in Next Generation Sequencing",
"doi": null,
"abstractUrl": "/journal/tb/2017/06/07501834/13rRUIM2VAj",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cluster/2018/8319/0/831900a637",
"title": "Simulating SVE-Optimised Genomics Workloads on Gem5",
"doi": null,
"abstractUrl": "/proceedings-article/cluster/2018/831900a637/17D45VsBTYI",
"parentPublication": {
"id": "proceedings/cluster/2018/8319/0",
"title": "2018 IEEE International Conference on Cluster Computing (CLUSTER)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bdcat/2018/5502/0/550200a041",
"title": "ntPack: A Software Package for Big Data in Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/bdcat/2018/550200a041/17D45XDIXRG",
"parentPublication": {
"id": "proceedings/bdcat/2018/5502/0",
"title": "2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2018/8161/0/08633632",
"title": "Business Management System for Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2018/08633632/17D45XwUAKG",
"parentPublication": {
"id": "proceedings/iisa/2018/8161/0",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669752",
"title": "Evaluation of using WGS/WES to characterize ACMG actionable genes in genetic testing reports",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669752/1A9WmkyH8JO",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/01/09702707",
"title": "Guest Editorial: Deep Learning For Genomics",
"doi": null,
"abstractUrl": "/journal/tb/2022/01/09702707/1AH3dAEy5C8",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ispass/2021/8643/0/864300a001",
"title": "GenomicsBench: A Benchmark Suite for Genomics",
"doi": null,
"abstractUrl": "/proceedings-article/ispass/2021/864300a001/1taFjml1coU",
"parentPublication": {
"id": "proceedings/ispass/2021/8643/0",
"title": "2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J9BjbjnEFq",
"title": "2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX)",
"acronym": "trex",
"groupId": "9973807",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J9BlQvVmdq",
"doi": "10.1109/TREX57753.2022.00007",
"title": "Kicking Analysts Out of the Meeting Room: Supporting Future Data-driven Decision Making with Intelligent Interactive Visualization Systems",
"normalizedTitle": "Kicking Analysts Out of the Meeting Room: Supporting Future Data-driven Decision Making with Intelligent Interactive Visualization Systems",
"abstract": "Today's data-driven decisions are largely dependent on professional analysts conducting analysis and generating visualizations for decision makers. These middlemen between data and decision makers may induce cost and trust issues in the generated visualizations. To overcome these issues, I envision a future scenario where intelligent interactive visualization systems may replace analysts in the decision-making process when the analyses and visualizations are relatively simple. However, three gaps need to be addressed before the future scenario could be realized. In this paper, I will discuss these gaps, propose potential solutions, and hope to raise a discussion on the future role of visualization systems for data-driven decision-making.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Today's data-driven decisions are largely dependent on professional analysts conducting analysis and generating visualizations for decision makers. These middlemen between data and decision makers may induce cost and trust issues in the generated visualizations. To overcome these issues, I envision a future scenario where intelligent interactive visualization systems may replace analysts in the decision-making process when the analyses and visualizations are relatively simple. However, three gaps need to be addressed before the future scenario could be realized. In this paper, I will discuss these gaps, propose potential solutions, and hope to raise a discussion on the future role of visualization systems for data-driven decision-making.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Today's data-driven decisions are largely dependent on professional analysts conducting analysis and generating visualizations for decision makers. These middlemen between data and decision makers may induce cost and trust issues in the generated visualizations. To overcome these issues, I envision a future scenario where intelligent interactive visualization systems may replace analysts in the decision-making process when the analyses and visualizations are relatively simple. However, three gaps need to be addressed before the future scenario could be realized. In this paper, I will discuss these gaps, propose potential solutions, and hope to raise a discussion on the future role of visualization systems for data-driven decision-making.",
"fno": "935600a016",
"keywords": [
"Data Visualisation",
"Decision Making",
"Data Driven Decision Making",
"Decision Makers",
"Intelligent Interactive Visualization Systems",
"Kicking Analysts",
"Meeting Room",
"Professional Analysts",
"Trust Issues",
"Data Analysis",
"Costs",
"Visual Analytics",
"Conferences",
"Decision Making",
"Data Visualization",
"Interactive Visualization",
"Business Intelligence",
"Data Driven Decisions",
"Human Centered Computing",
"Visualization",
"Visualization Application Domains",
"Visual Analytics"
],
"authors": [
{
"affiliation": "National Sun Yat-sen University",
"fullName": "Yi Han",
"givenName": "Yi",
"surname": "Han",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "trex",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "16-21",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-9356-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1J9BlMFuiXe",
"name": "ptrex202293560-09974313s1-mm_935600a016.zip",
"size": "92.9 kB",
"location": "https://www.computer.org/csdl/api/v1/extra/ptrex202293560-09974313s1-mm_935600a016.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "935600a008",
"articleId": "1J9BkDHcAz6",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "935600a067",
"articleId": "1J9BjyQ6g6Y",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wsc/2003/8131/2/01261538",
"title": "Caveats for simulation modeling in support of decision making",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/2003/01261538/12OmNAPSMlO",
"parentPublication": {
"id": "proceedings/wsc/2003/8131/2",
"title": "Proceedings of the 2003 Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/eisic/2011/4406/0/4406a291",
"title": "Decision Support System for Intelligence Analysts",
"doi": null,
"abstractUrl": "/proceedings-article/eisic/2011/4406a291/12OmNBSjJ2u",
"parentPublication": {
"id": "proceedings/eisic/2011/4406/0",
"title": "European Intelligence and Security Informatics Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2013/4892/0/4892b485",
"title": "Aperture: An Open Web 2.0 Visualization Framework",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2013/4892b485/12OmNCgrD1q",
"parentPublication": {
"id": "proceedings/hicss/2013/4892/0",
"title": "2013 46th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2013/4892/0/4892c416",
"title": "Visual Analytics for Public Health: Supporting Knowledge Construction and Decision-Making",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2013/4892c416/12OmNrJiCNq",
"parentPublication": {
"id": "proceedings/hicss/2013/4892/0",
"title": "2013 46th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/eisic/2016/2857/0/07870207",
"title": "How Analysts Think: Decision Making in the Absence of Clear Facts",
"doi": null,
"abstractUrl": "/proceedings-article/eisic/2016/07870207/12OmNvlxJs3",
"parentPublication": {
"id": "proceedings/eisic/2016/2857/0",
"title": "2016 European Intelligence and Security Informatics Conference (EISIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2012/4752/0/06400507",
"title": "Agile visual analytics for banking cyber “big data”",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2012/06400507/12OmNyPQ4EL",
"parentPublication": {
"id": "proceedings/vast/2012/4752/0",
"title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875970",
"title": "Proactive Spatiotemporal Resource Allocation and Predictive Visual Analytics for Community Policing and Law Enforcement",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875970/13rRUNvgyWo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2011/10/mco2011100084",
"title": "From Data Analysis and Visualization to Causality Discovery",
"doi": null,
"abstractUrl": "/magazine/co/2011/10/mco2011100084/13rRUwbaqOQ",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2014/05/mcg2014050042",
"title": "From Data to Insight: Work Practices of Analysts in the Enterprise",
"doi": null,
"abstractUrl": "/magazine/cg/2014/05/mcg2014050042/13rRUyXKxU9",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/09/09321557",
"title": "Task-Based Visual Interactive Modeling: Decision Trees and Rule-Based Classifiers",
"doi": null,
"abstractUrl": "/journal/tg/2022/09/09321557/1qmbp8bk4FO",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAR1b14",
"title": "Proceedings of IEEE Scalable High Performance Computing Conference",
"acronym": "shpcc",
"groupId": "1000642",
"volume": "0",
"displayVolume": "0",
"year": "1994",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNxX3ush",
"doi": "10.1109/SHPCC.1994.296631",
"title": "Scalable implementations of multipole-accelerated algorithms for molecular dynamics",
"normalizedTitle": "Scalable implementations of multipole-accelerated algorithms for molecular dynamics",
"abstract": "We consider efficient, scalable solutions to the long-range force computation problem in molecular dynamics (MD) simulation. Straightforward implementation of a solver for the time-consuming Coulomb force yields O(N/sup 2/) runtime for N atoms in a system; this quadratic complexity limits the size of systems that can be simulated. Exclusion of interactions beyond a certain cutoff radius reduces runtime but also negatively impacts simulation accuracy. By using algorithms based on the multipole expansion of the potential due to groups of charged particles, the work permits high-accuracy simulations which include all pair interactions (i.e. no truncation) at a runtime cost which grows linearly with the size of the system. The algorithms are parallelizable on a range of platforms; we concentrate on the Kendall Square KSR-1. We present results from four variants of the multipole-accelerated algorithms on systems of up to a million particles on up to 32 processors.<>",
"abstracts": [
{
"abstractType": "Regular",
"content": "We consider efficient, scalable solutions to the long-range force computation problem in molecular dynamics (MD) simulation. Straightforward implementation of a solver for the time-consuming Coulomb force yields O(N/sup 2/) runtime for N atoms in a system; this quadratic complexity limits the size of systems that can be simulated. Exclusion of interactions beyond a certain cutoff radius reduces runtime but also negatively impacts simulation accuracy. By using algorithms based on the multipole expansion of the potential due to groups of charged particles, the work permits high-accuracy simulations which include all pair interactions (i.e. no truncation) at a runtime cost which grows linearly with the size of the system. The algorithms are parallelizable on a range of platforms; we concentrate on the Kendall Square KSR-1. We present results from four variants of the multipole-accelerated algorithms on systems of up to a million particles on up to 32 processors.<>",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We consider efficient, scalable solutions to the long-range force computation problem in molecular dynamics (MD) simulation. Straightforward implementation of a solver for the time-consuming Coulomb force yields O(N/sup 2/) runtime for N atoms in a system; this quadratic complexity limits the size of systems that can be simulated. Exclusion of interactions beyond a certain cutoff radius reduces runtime but also negatively impacts simulation accuracy. By using algorithms based on the multipole expansion of the potential due to groups of charged particles, the work permits high-accuracy simulations which include all pair interactions (i.e. no truncation) at a runtime cost which grows linearly with the size of the system. The algorithms are parallelizable on a range of platforms; we concentrate on the Kendall Square KSR-1. We present results from four variants of the multipole-accelerated algorithms on systems of up to a million particles on up to 32 processors.",
"fno": "00296631",
"keywords": [
"Molecular Dynamics Method",
"Physics Computing",
"Physics",
"Digital Simulation",
"Computational Complexity",
"Parallel Algorithms",
"Scalable Implementations",
"Multipole Accelerated Algorithms",
"Molecular Dynamics",
"Long Range Force Computation Problem",
"MD Simulation",
"Quadratic Complexity",
"Runtime",
"Simulation Accuracy",
"Multipole Expansion",
"Charged Particles",
"All Pair Interactions",
"Parallelizable",
"Kendall Square KSR 1",
"Parallel Algorithms",
"Heuristic Algorithms",
"Computational Modeling",
"Runtime",
"Atomic Measurements",
"Costs",
"Biology Computing",
"Biological System Modeling",
"Biological Information Theory",
"Proteins",
"Hardware"
],
"authors": [
{
"affiliation": "Dept. of Electr. Eng., Duke Univ., Durham, NC, USA",
"fullName": "J.A. Board",
"givenName": "J.A.",
"surname": "Board",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Electr. Eng., Duke Univ., Durham, NC, USA",
"fullName": "Z.S. Hakura",
"givenName": "Z.S.",
"surname": "Hakura",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Electr. Eng., Duke Univ., Durham, NC, USA",
"fullName": "W.D. Elliott",
"givenName": "W.D.",
"surname": "Elliott",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Electr. Eng., Duke Univ., Durham, NC, USA",
"fullName": "D.C. Gray",
"givenName": "D.C.",
"surname": "Gray",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Electr. Eng., Duke Univ., Durham, NC, USA",
"fullName": "W.J. Blanke",
"givenName": "W.J.",
"surname": "Blanke",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Electr. Eng., Duke Univ., Durham, NC, USA",
"fullName": "J.F. Leathrum",
"givenName": "J.F.",
"surname": "Leathrum",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "shpcc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1994-01-01T00:00:00",
"pubType": "proceedings",
"pages": "87,88,89,90,91,92,93,94",
"year": "1994",
"issn": null,
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "00296630",
"articleId": "12OmNBO3Kl1",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "00296632",
"articleId": "12OmNxGSm3q",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sc/1999/1966/0/19660056",
"title": "Large Scale Molecular Dynamics Simulations with Fast Multipole Implementations",
"doi": null,
"abstractUrl": "/proceedings-article/sc/1999/19660056/12OmNAhOULr",
"parentPublication": {
"id": "proceedings/sc/1999/1966/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sccompanion/2012/4956/0/4956a617",
"title": "A Task Parallel Implementation of Fast Multipole Methods",
"doi": null,
"abstractUrl": "/proceedings-article/sccompanion/2012/4956a617/12OmNBKW9DG",
"parentPublication": {
"id": "proceedings/sccompanion/2012/4956/0",
"title": "2012 SC Companion: High Performance Computing, Networking Storage and Analysis",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcs/2017/3250/0/08035094",
"title": "Parallel Adaptively Restrained Molecular Dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/hpcs/2017/08035094/12OmNqBbHUD",
"parentPublication": {
"id": "proceedings/hpcs/2017/3250/0",
"title": "2017 International Conference on High-Performance Computing & Simulation (HPCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scc/2012/6218/0/06495868",
"title": "A Task Parallel Implementation of Fast Multipole Methods",
"doi": null,
"abstractUrl": "/proceedings-article/scc/2012/06495868/12OmNqIzgTx",
"parentPublication": {
"id": "proceedings/scc/2012/6218/0",
"title": "2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ispdc/2012/2599/0/06341510",
"title": "Scalable Force Directed Graph Layout Algorithms Using Fast Multipole Methods",
"doi": null,
"abstractUrl": "/proceedings-article/ispdc/2012/06341510/12OmNx3HI8B",
"parentPublication": {
"id": "proceedings/ispdc/2012/2599/0",
"title": "2012 11th International Symposium on Parallel and Distributed Computing (ISPDC 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scalcom-embeddedcom/2009/3825/0/3825a360",
"title": "FPGA-Accelerated Molecular Dynamics Simulations System",
"doi": null,
"abstractUrl": "/proceedings-article/scalcom-embeddedcom/2009/3825a360/12OmNx7ouYp",
"parentPublication": {
"id": "proceedings/scalcom-embeddedcom/2009/3825/0",
"title": "Scalable Computing and Communications; International Conference on Embedded Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpdc/1996/7582/0/75820040",
"title": "A Massively Parallel Fast Multipole Algorithm in Three Dimensions",
"doi": null,
"abstractUrl": "/proceedings-article/hpdc/1996/75820040/12OmNyL0TN7",
"parentPublication": {
"id": "proceedings/hpdc/1996/7582/0",
"title": "Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipdpsw/2014/4116/0/4116a966",
"title": "Scalable Fast Multipole Accelerated Vortex Methods",
"doi": null,
"abstractUrl": "/proceedings-article/ipdpsw/2014/4116a966/12OmNyTwRcH",
"parentPublication": {
"id": "proceedings/ipdpsw/2014/4116/0",
"title": "2014 IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPSW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/1999/1966/0/01592699",
"title": "Large Scale Molecular Dynamics Simulations with Fast Multipole Implementations",
"doi": null,
"abstractUrl": "/proceedings-article/sc/1999/01592699/1D85QNCwDYs",
"parentPublication": {
"id": "proceedings/sc/1999/1966/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asap/2019/1601/0/160100a263",
"title": "Molecular Dynamics Range-Limited Force Evaluation Optimized for FPGAs",
"doi": null,
"abstractUrl": "/proceedings-article/asap/2019/160100a263/1d5kFrWjsvC",
"parentPublication": {
"id": "proceedings/asap/2019/1601/2160-052X",
"title": "2019 IEEE 30th International Conference on Application-specific Systems, Architectures and Processors (ASAP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNrF2DI6",
"title": "2011 IEEE Symposium on Biological Data Visualization (BioVis).",
"acronym": "biovis",
"groupId": "1800574",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzSQdnY",
"doi": "10.1109/BioVis.2011.6094055",
"title": "MDMap: A system for data-driven layout and exploration of molecular dynamics simulations",
"normalizedTitle": "MDMap: A system for data-driven layout and exploration of molecular dynamics simulations",
"abstract": "Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains.",
"fno": "111118patro",
"keywords": [
"Stochastic Processes",
"Biology Computing",
"Digital Simulation",
"Graph Theory",
"Molecular Dynamics Method",
"Stochastic Time Varying Simulations",
"MD Map",
"Data Driven Layout",
"Data Driven Exploration",
"Molecular Dynamics Simulations",
"State Transition Graph",
"Trajectory Space",
"Biomolecular Folding Landscapes",
"Layout",
"Visualization",
"Biological System Modeling",
"Computational Modeling",
"Proteins",
"Data Visualization",
"Trajectory",
"Clustering",
"Molecular Dynamics",
"Protein Folding",
"Time Varying Visualization",
"Graph Layout",
"Bioinformatics"
],
"authors": [
{
"affiliation": "Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA",
"fullName": "R. Patro",
"givenName": "R.",
"surname": "Patro",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA",
"fullName": "Cheuk Yiu Ip",
"givenName": null,
"surname": "Cheuk Yiu Ip",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA",
"fullName": "S. Bista",
"givenName": "S.",
"surname": "Bista",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "S. S. Cho",
"givenName": "S. S.",
"surname": "Cho",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Biophys. Program, Univ. of Maryland, College Park, MD, USA",
"fullName": "D. Thirumalai",
"givenName": "D.",
"surname": "Thirumalai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA",
"fullName": "A. Varshney",
"givenName": "A.",
"surname": "Varshney",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "biovis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2011-10-01T00:00:00",
"pubType": "proceedings",
"pages": "111-118",
"year": "2011",
"issn": null,
"isbn": "978-1-4673-0003-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "103110smith",
"articleId": "12OmNwDj1hM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "119126paterson",
"articleId": "12OmNwFRp7K",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fccm/2008/3307/0/3307a248",
"title": "An Efficient O(1) Priority Queue for Large FPGA-Based Discrete Event Simulations of Molecular Dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/fccm/2008/3307a248/12OmNAYXWLA",
"parentPublication": {
"id": "proceedings/fccm/2008/3307/0",
"title": "2008 16th International Symposium on Field-Programmable Custom Computing Machines",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/1996/2642/0/26420050",
"title": "Lightweight Computational Steering of Very Large Scale Molecular Dynamics Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/sc/1996/26420050/12OmNB7tUr3",
"parentPublication": {
"id": "proceedings/sc/1996/2642/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cit/2009/3836/2/3836b254",
"title": "GPU Acceleration of High-Speed Collision Molecular Dynamics Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/cit/2009/3836b254/12OmNBSBk4o",
"parentPublication": {
"id": "proceedings/cit/2009/3836/2",
"title": "Computer and Information Technology, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asap/2009/3732/0/3732a129",
"title": "Parallel Discrete Event Simulation of Molecular Dynamics Through Event-Based Decomposition",
"doi": null,
"abstractUrl": "/proceedings-article/asap/2009/3732a129/12OmNCmGNR2",
"parentPublication": {
"id": "proceedings/asap/2009/3732/0",
"title": "2009 20th IEEE International Conference on Application-specific Systems, Architectures and Processors",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fpl/2005/9362/0/01515767",
"title": "Accelerating molecular dynamics simulations with configurable circuits",
"doi": null,
"abstractUrl": "/proceedings-article/fpl/2005/01515767/12OmNvkYx9J",
"parentPublication": {
"id": "proceedings/fpl/2005/9362/0",
"title": "Proceedings. 2005 International Conference on Field Programmable Logic and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdcat/2008/3443/0/3443a143",
"title": "Overheads in Accelerating Molecular Dynamics Simulations with GPUs",
"doi": null,
"abstractUrl": "/proceedings-article/pdcat/2008/3443a143/12OmNx57HQG",
"parentPublication": {
"id": "proceedings/pdcat/2008/3443/0",
"title": "2008 Ninth International Conference on Parallel and Distributed Computing, Applications and Technologies",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scalcom-embeddedcom/2009/3825/0/3825a360",
"title": "FPGA-Accelerated Molecular Dynamics Simulations System",
"doi": null,
"abstractUrl": "/proceedings-article/scalcom-embeddedcom/2009/3825a360/12OmNx7ouYp",
"parentPublication": {
"id": "proceedings/scalcom-embeddedcom/2009/3825/0",
"title": "Scalable Computing and Communications; International Conference on Embedded Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ams/2008/3136/0/3136a895",
"title": "Unravelling Prion Diseases Using Molecular Dynamics Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/ams/2008/3136a895/12OmNxbmSBI",
"parentPublication": {
"id": "proceedings/ams/2008/3136/0",
"title": "Asia International Conference on Modelling & Simulation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipps/1995/7074/0/70740053",
"title": "Monte Carlo and molecular dynamics simulations using p4",
"doi": null,
"abstractUrl": "/proceedings-article/ipps/1995/70740053/12OmNzdoMvS",
"parentPublication": {
"id": "proceedings/ipps/1995/7074/0",
"title": "Proceedings of 9th International Parallel Processing Symposium",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dl/2019/6011/0/08945122",
"title": "DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding",
"doi": null,
"abstractUrl": "/proceedings-article/dl/2019/08945122/1grNxhdN8Ry",
"parentPublication": {
"id": "proceedings/dl/2019/6011/0",
"title": "2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J4Cea0Cpaw",
"title": "2022 IEEE International Symposium on Workload Characterization (IISWC)",
"acronym": "iiswc",
"groupId": "1000819",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J4CgdGq9vG",
"doi": "10.1109/IISWC55918.2022.00016",
"title": "Characterizing Molecular Dynamics Simulation on Commodity Platforms",
"normalizedTitle": "Characterizing Molecular Dynamics Simulation on Commodity Platforms",
"abstract": "Molecular Dynamics (MD) simulation is an essential tool driving innovation in key scientific domains such as physics, materials science, biochemistry, and drug discovery. Enabling larger, longer, and more accurate MD simulations can directly impact scientific discovery and innovation. While domain-specific architectures for MD exist, they are not widely accessible, and MD performance on commodity platforms (i.e., CPUs and GPUs) remains critical for supporting broad and agile scientific progress. This paper aims at characterizing MD simulation on commodity platforms with a benchmark campaign on modern systems available in public cloud offerings. We focus on LAMMPS, one of the prevalent MD frameworks, and characterize several representative and diverse MD experiments. We find that the benchmarked CPU instance provides good scalability to many cores, while the reference LAMMPS GPU implementation struggles with scaling to multiple devices. Additionally, we evaluate the performance impact of application-specific parameters such as error threshold and arithmetic precision. Our study indicates that key drivers for further improvement of LAMMPS performance on commodity systems are: 1) improving scalability and offload efficiency in multi-accelerator systems and 2) reducing work imbalance in the CPU parallelization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Molecular Dynamics (MD) simulation is an essential tool driving innovation in key scientific domains such as physics, materials science, biochemistry, and drug discovery. Enabling larger, longer, and more accurate MD simulations can directly impact scientific discovery and innovation. While domain-specific architectures for MD exist, they are not widely accessible, and MD performance on commodity platforms (i.e., CPUs and GPUs) remains critical for supporting broad and agile scientific progress. This paper aims at characterizing MD simulation on commodity platforms with a benchmark campaign on modern systems available in public cloud offerings. We focus on LAMMPS, one of the prevalent MD frameworks, and characterize several representative and diverse MD experiments. We find that the benchmarked CPU instance provides good scalability to many cores, while the reference LAMMPS GPU implementation struggles with scaling to multiple devices. Additionally, we evaluate the performance impact of application-specific parameters such as error threshold and arithmetic precision. Our study indicates that key drivers for further improvement of LAMMPS performance on commodity systems are: 1) improving scalability and offload efficiency in multi-accelerator systems and 2) reducing work imbalance in the CPU parallelization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Molecular Dynamics (MD) simulation is an essential tool driving innovation in key scientific domains such as physics, materials science, biochemistry, and drug discovery. Enabling larger, longer, and more accurate MD simulations can directly impact scientific discovery and innovation. While domain-specific architectures for MD exist, they are not widely accessible, and MD performance on commodity platforms (i.e., CPUs and GPUs) remains critical for supporting broad and agile scientific progress. This paper aims at characterizing MD simulation on commodity platforms with a benchmark campaign on modern systems available in public cloud offerings. We focus on LAMMPS, one of the prevalent MD frameworks, and characterize several representative and diverse MD experiments. We find that the benchmarked CPU instance provides good scalability to many cores, while the reference LAMMPS GPU implementation struggles with scaling to multiple devices. Additionally, we evaluate the performance impact of application-specific parameters such as error threshold and arithmetic precision. Our study indicates that key drivers for further improvement of LAMMPS performance on commodity systems are: 1) improving scalability and offload efficiency in multi-accelerator systems and 2) reducing work imbalance in the CPU parallelization.",
"fno": "879800a065",
"keywords": [
"Cloud Computing",
"Computer Graphic Equipment",
"Coprocessors",
"Graphics Processing Units",
"Molecular Dynamics Method",
"Multiprocessing Systems",
"Parallel Architectures",
"Parallel Processing",
"Agile Scientific Progress",
"Application Specific Parameters",
"Benchmark Campaign",
"Benchmarked CPU Instance",
"Broad Progress",
"Characterizing MD Simulation",
"Characterizing Molecular Dynamics Simulation",
"Commodity Platforms",
"Commodity Systems",
"Diverse MD Experiments",
"Domain Specific Architectures",
"Drug Discovery",
"Essential Tool Driving Innovation",
"Key Scientific Domains",
"LAMMPS Performance",
"Materials Science",
"MD Performance",
"Performance Impact",
"Prevalent MD Frameworks",
"Public Cloud Offerings",
"Reference LAMMPS GPU Implementation",
"Representative Experiments",
"Scientific Discovery",
"Performance Evaluation",
"Drugs",
"Technological Innovation",
"Materials Science And Technology",
"Cloud Computing",
"Scalability",
"Biological System Modeling",
"LAMMPS",
"Molecular Dynamics",
"Workload Characterization",
"HPC",
"Profiling"
],
"authors": [
{
"affiliation": "DEIB, Politecnico di Milano,Italy",
"fullName": "Francesco Peverelli",
"givenName": "Francesco",
"surname": "Peverelli",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "DEIB, Politecnico di Milano,Italy",
"fullName": "Davide Conficconi",
"givenName": "Davide",
"surname": "Conficconi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Systems Laboratory, Zurich Research Center, Huawei Technologies,Switzerland",
"fullName": "Davide Basilio Bartolini",
"givenName": "Davide Basilio",
"surname": "Bartolini",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Systems Laboratory, Zurich Research Center, Huawei Technologies,Switzerland",
"fullName": "Alberto Scolari",
"givenName": "Alberto",
"surname": "Scolari",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "DEIB, Politecnico di Milano,Italy",
"fullName": "Marco Domenico Santambrogio",
"givenName": "Marco Domenico",
"surname": "Santambrogio",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iiswc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-11-01T00:00:00",
"pubType": "proceedings",
"pages": "65-78",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-8798-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "879800a051",
"articleId": "1J4CgUieR68",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "879800a079",
"articleId": "1J4CflEXsEo",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/hpcs/2017/3250/0/08035094",
"title": "Parallel Adaptively Restrained Molecular Dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/hpcs/2017/08035094/12OmNqBbHUD",
"parentPublication": {
"id": "proceedings/hpcs/2017/3250/0",
"title": "2017 International Conference on High-Performance Computing & Simulation (HPCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcc-icess/2012/4749/0/4749a959",
"title": "Comparison Studies of Large-scale Conventional Molecular Dynamics Simulation on Parallel Machines",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-icess/2012/4749a959/12OmNroijlN",
"parentPublication": {
"id": "proceedings/hpcc-icess/2012/4749/0",
"title": "High Performance Computing and Communication & IEEE International Conference on Embedded Software and Systems, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcc/2016/4297/0/07828411",
"title": "Implementing Molecular Dynamics Simulation on Sunway TaihuLight System",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc/2016/07828411/12OmNxj2399",
"parentPublication": {
"id": "proceedings/hpcc/2016/4297/0",
"title": "2016 IEEE 18th International Conference on High-Performance Computing and Communications, IEEE 14th International Conference on Smart City, and IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2019/05/08254322",
"title": "Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis",
"doi": null,
"abstractUrl": "/magazine/cs/2019/05/08254322/13rRUyoyhJI",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2006/2700/0/04090217",
"title": "Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2006/04090217/17D45VTRowC",
"parentPublication": {
"id": "proceedings/sc/2006/2700/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a027",
"title": "MDZ: An Efficient Error-bounded Lossy Compressor for Molecular Dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a027/1FwFEICGMWA",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2021/8442/0/09910135",
"title": "Billion atom molecular dynamics simulations of carbon at extreme conditions and experimental time and length scales",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2021/09910135/1HzBF4E3Dbi",
"parentPublication": {
"id": "proceedings/sc/2021/8442/0",
"title": "SC21: International Conference for High Performance Computing, Networking, Storage and Analysis",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcc-dss-smartcity-dependsys/2022/1993/0/199300a051",
"title": "MISA-MD: A New Design of Molecular Dynamics Software for GPU Architecture *",
"doi": null,
"abstractUrl": "/proceedings-article/hpcc-dss-smartcity-dependsys/2022/199300a051/1LSPEq38oqA",
"parentPublication": {
"id": "proceedings/hpcc-dss-smartcity-dependsys/2022/1993/0",
"title": "2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/escience/2019/2451/0/245100a188",
"title": "Characterizing In Situ and In Transit Analytics of Molecular Dynamics Simulations for Next-Generation Supercomputers",
"doi": null,
"abstractUrl": "/proceedings-article/escience/2019/245100a188/1ike1Fvh6Te",
"parentPublication": {
"id": "proceedings/escience/2019/2451/0",
"title": "2019 15th International Conference on eScience (eScience)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2020/1485/0/148500b074",
"title": "Commodity Search Algorithm based on Ant Colony Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/ispa-bdcloud-socialcom-sustaincom/2020/148500b074/1ua4MFeoS8U",
"parentPublication": {
"id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2020/1485/0",
"title": "2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1cpqjBXCukg",
"title": "2019 IEEE Pacific Visualization Symposium (PacificVis)",
"acronym": "pacificvis",
"groupId": "1001657",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1cMF88klX8c",
"doi": "10.1109/PacificVis.2019.00032",
"title": "Visual Analysis of Ligand Trajectories in Molecular Dynamics",
"normalizedTitle": "Visual Analysis of Ligand Trajectories in Molecular Dynamics",
"abstract": "In many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.",
"fno": "922600a212",
"keywords": [
"Biology Computing",
"Chemistry Computing",
"Data Visualisation",
"Interactive Systems",
"Molecular Biophysics",
"Proteins",
"Interactive Filtering",
"Buried Active Site",
"Protein Engineers",
"Protein Reactions",
"Functional Boxplot",
"Interactive Visual Analysis",
"Interactive Exploration",
"Trajectory Properties",
"Ligand Trajectories",
"Interactive Visual Exploration",
"Ligand Motion",
"Trajectory",
"Proteins",
"Visualization",
"Tools",
"Two Dimensional Displays",
"Data Visualization",
"Three Dimensional Displays",
"Visualization",
"Trajectory",
"Protein",
"Ligand"
],
"authors": [
{
"affiliation": "Masaryk University",
"fullName": "Adam Jurčík",
"givenName": "Adam",
"surname": "Jurčík",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Masaryk University",
"fullName": "Katarína Furmanová",
"givenName": "Katarína",
"surname": "Furmanová",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Bergen, Masaryk Universtiy",
"fullName": "Jan Byška",
"givenName": "Jan",
"surname": "Byška",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Czech Technical University",
"fullName": "Vojtěch Vonásek",
"givenName": "Vojtěch",
"surname": "Vonásek",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Masaryk University, FNUSA-ICRC",
"fullName": "Ondřej Vávra",
"givenName": "Ondřej",
"surname": "Vávra",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Masaryk University",
"fullName": "Pavol Ulbrich",
"givenName": "Pavol",
"surname": "Ulbrich",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Bergen",
"fullName": "Helwig Hauser",
"givenName": "Helwig",
"surname": "Hauser",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Masaryk University",
"fullName": "Barbora Kozlíková",
"givenName": "Barbora",
"surname": "Kozlíková",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "pacificvis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-04-01T00:00:00",
"pubType": "proceedings",
"pages": "212-221",
"year": "2019",
"issn": null,
"isbn": "978-1-5386-9226-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "922600a184",
"articleId": "1cMF7eHg3Cg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "922600a247",
"articleId": "1cMF72Dj1Sg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibe/2017/1324/0/132401a352",
"title": "CALI: A Novel Visual Model for Frequent Pattern Mining in Protein-Ligand Graphs",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2017/132401a352/12OmNBpVQag",
"parentPublication": {
"id": "proceedings/bibe/2017/1324/0",
"title": "2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2016/5910/0/07836675",
"title": "Ligand-Based Virtual Screening with Co-regularised Support Vector Regression",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2016/07836675/12OmNyOq514",
"parentPublication": {
"id": "proceedings/icdmw/2016/5910/0",
"title": "2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539331",
"title": "Physics-Based Visual Characterization of Molecular Interaction Forces",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539331/13rRUwjGoLJ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2020/04/08606950",
"title": "nAPOLI: A Graph-Based Strategy to Detect and Visualize Conserved Protein-Ligand Interactions in Large-Scale",
"doi": null,
"abstractUrl": "/journal/tb/2020/04/08606950/17D45W9KVHi",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08456856",
"title": "Visualization of Large Molecular Trajectories",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08456856/17D45Xbl4Qi",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669761",
"title": "Understanding the binding of the same ligand to GPCRs of different families",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669761/1A9Vm2u8XIc",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995694",
"title": "ViTRMSE: a three-dimensional RMSE scoring method for protein-ligand docking models based on Vision Transformer",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995694/1JC2Y3vgrv2",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020490",
"title": "APIP: Attention-based Protein Representation Learning for Protein-Ligand Interface Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020490/1KfQZNOjXig",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/5555/01/10026482",
"title": "GraphPLBR: Protein-ligand Binding Residue Prediction with Deep Graph Convolution Network",
"doi": null,
"abstractUrl": "/journal/tb/5555/01/10026482/1KkXbe3yD7i",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/01/09305294",
"title": "Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction",
"doi": null,
"abstractUrl": "/journal/tb/2022/01/09305294/1pNki2dvKda",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1hJrHq07uw0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"acronym": "big-data",
"groupId": "1802964",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1hJsu4lY0PS",
"doi": "10.1109/BigData47090.2019.9006048",
"title": "Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations",
"normalizedTitle": "Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations",
"abstract": "Molecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).",
"abstracts": [
{
"abstractType": "Regular",
"content": "Molecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Molecular Dynamics (MD) simulation have been emerging as an excellent candidate for understanding complex atomic and molecular scale mechanism of bio-molecules that control essential bio-physical phenomenon in a living organism. But this MD technique produces large-size and long-timescale data that are inherently high-dimensional and occupies many terabytes of data. Processing this immense amount of data in a meaningful way is becoming increasingly difficult. Therefore, specific dimensionality reduction algorithm using deep learning technique has been employed here to embed the high-dimensional data in a lower-dimension latent space that still preserves the inherent molecular characteristics i.e. retains biologically meaningful information. Subsequently, the results of the embedding models are visualized for model evaluation and analysis of the extracted underlying features. However, most of the existing visualizations for embeddings have limitations in evaluating the embedding models and understanding the complex simulation data. We propose an interactive visual analytics system for embeddings of MD simulations to not only evaluate and explain an embedding model but also analyze various characteristics of the simulations. Our system enables exploration and discovery of meaningful and semantic embedding results and supports the understanding and evaluation of results by the quantitatively described features of the MD simulations (even without specific labels).",
"fno": "09006048",
"keywords": [
"Biology Computing",
"Data Analysis",
"Data Visualisation",
"Learning Artificial Intelligence",
"Molecular Dynamics Method",
"Large Scale Molecular Dynamics Simulations",
"Complex Atomic Scale Mechanism",
"Molecular Scale Mechanism",
"Bio Molecules",
"Essential Bio Physical Phenomenon",
"Living Organism",
"MD Technique",
"Long Timescale Data",
"Specific Dimensionality Reduction Algorithm",
"Deep Learning Technique",
"High Dimensional Data",
"Lower Dimension Latent Space",
"Inherent Molecular Characteristics",
"Embedding Model",
"Complex Simulation Data",
"Interactive Visual Analytics System",
"MD Simulations",
"Semantic Embedding",
"Feature Extraction",
"Biological System Modeling",
"Three Dimensional Displays",
"Analytical Models",
"Data Visualization",
"Shape",
"Data Models",
"Proteins",
"Visual Analytics",
"Machine Learning",
"HCI",
"Molecular Dynamics"
],
"authors": [
{
"affiliation": "Oak Ridge National Laboratory,Oak Ridge,USA",
"fullName": "Junghoon Chae",
"givenName": "Junghoon",
"surname": "Chae",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Oak Ridge National Laboratory,Oak Ridge,USA",
"fullName": "Debsindhu Bhowmik",
"givenName": "Debsindhu",
"surname": "Bhowmik",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Argonne National Laboratory,Lemont,USA",
"fullName": "Heng Ma",
"givenName": "Heng",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Argonne National Laboratory,Lemont,USA",
"fullName": "Arvind Ramanathan",
"givenName": "Arvind",
"surname": "Ramanathan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Oak Ridge National Laboratory,Oak Ridge,USA",
"fullName": "Chad Steed",
"givenName": "Chad",
"surname": "Steed",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "big-data",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-12-01T00:00:00",
"pubType": "proceedings",
"pages": "1759-1764",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-0858-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09006271",
"articleId": "1hJrO8e1KPm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09006115",
"articleId": "1hJsdeaOrJu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ucc/2014/7881/0/7881a579",
"title": "A Cloud-Based Data Farming Platform for Molecular Dynamics Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/ucc/2014/7881a579/12OmNvStcP5",
"parentPublication": {
"id": "proceedings/ucc/2014/7881/0",
"title": "2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fpl/2005/9362/0/01515767",
"title": "Accelerating molecular dynamics simulations with configurable circuits",
"doi": null,
"abstractUrl": "/proceedings-article/fpl/2005/01515767/12OmNvkYx9J",
"parentPublication": {
"id": "proceedings/fpl/2005/9362/0",
"title": "Proceedings. 2005 International Conference on Field Programmable Logic and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sbac-pad/2004/2240/0/01364748",
"title": "A parallel engine for graphical interactive molecular dynamics simulations",
"doi": null,
"abstractUrl": "/proceedings-article/sbac-pad/2004/01364748/12OmNwCaCua",
"parentPublication": {
"id": "proceedings/sbac-pad/2004/2240/0",
"title": "Computer Architecture and High Performance Computing, Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/biovis/2011/0003/0/111118patro",
"title": "MDMap: A system for data-driven layout and exploration of molecular dynamics simulations",
"doi": null,
"abstractUrl": "/proceedings-article/biovis/2011/111118patro/12OmNzSQdnY",
"parentPublication": {
"id": "proceedings/biovis/2011/0003/0",
"title": "2011 IEEE Symposium on Biological Data Visualization (BioVis).",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cahpc/2004/2240/0/01364748",
"title": "A parallel engine for graphical interactive molecular dynamics simulations",
"doi": null,
"abstractUrl": "/proceedings-article/cahpc/2004/01364748/12OmNzWfoRD",
"parentPublication": {
"id": "proceedings/cahpc/2004/2240/0",
"title": "Proceedings. 16th Symposium on Computer Architecture and High Performance Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2019/05/08254322",
"title": "Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis",
"doi": null,
"abstractUrl": "/magazine/cs/2019/05/08254322/13rRUyoyhJI",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a027",
"title": "MDZ: An Efficient Error-bounded Lossy Compressor for Molecular Dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a027/1FwFEICGMWA",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903280",
"title": "sMolBoxes: Dataflow Model for Molecular Dynamics Exploration",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903280/1GZojkUkomI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dl/2019/6011/0/08945122",
"title": "DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding",
"doi": null,
"abstractUrl": "/proceedings-article/dl/2019/08945122/1grNxhdN8Ry",
"parentPublication": {
"id": "proceedings/dl/2019/6011/0",
"title": "2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/escience/2019/2451/0/245100a188",
"title": "Characterizing In Situ and In Transit Analytics of Molecular Dynamics Simulations for Next-Generation Supercomputers",
"doi": null,
"abstractUrl": "/proceedings-article/escience/2019/245100a188/1ike1Fvh6Te",
"parentPublication": {
"id": "proceedings/escience/2019/2451/0",
"title": "2019 15th International Conference on eScience (eScience)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1ikdZO7kJFe",
"title": "2019 15th International Conference on eScience (eScience)",
"acronym": "escience",
"groupId": "1001511",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1ike1Fvh6Te",
"doi": "10.1109/eScience.2019.00027",
"title": "Characterizing In Situ and In Transit Analytics of Molecular Dynamics Simulations for Next-Generation Supercomputers",
"normalizedTitle": "Characterizing In Situ and In Transit Analytics of Molecular Dynamics Simulations for Next-Generation Supercomputers",
"abstract": "Molecular Dynamics (MD) simulations executed on state-of-the-art supercomputers are producing data at rates faster than it can be written out to disk. In situ and in transit analysis of data generated by MD simulations reduce the original volume of information by several orders of magnitude, thereby alleviating the negative impact of I/O bottlenecks. This work focuses on characterizing the impact of in situ and in transit analytics on the overall MD workflow performance, and the capability for capturing rapid, rare events in the simulated molecular system. The MD simulation and analysis processes share data via remote direct memory access (RDMA) using DataSpaces. Our metrics of interest are time spent waiting in I/O by the MD simulation, lost frames of the MD simulation, and idle time of the analysis. We measure these metrics for a diverse set of molecular systems and characterize their trends for in situ and in transit configurations. We then model which frames are dropped and which ones are analyzed for a real use case. The insights gained from this study are generally applicable for in situ and in transit workflows that require optimization of parameters to minimize loss in workflow performance and analytic accuracy.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Molecular Dynamics (MD) simulations executed on state-of-the-art supercomputers are producing data at rates faster than it can be written out to disk. In situ and in transit analysis of data generated by MD simulations reduce the original volume of information by several orders of magnitude, thereby alleviating the negative impact of I/O bottlenecks. This work focuses on characterizing the impact of in situ and in transit analytics on the overall MD workflow performance, and the capability for capturing rapid, rare events in the simulated molecular system. The MD simulation and analysis processes share data via remote direct memory access (RDMA) using DataSpaces. Our metrics of interest are time spent waiting in I/O by the MD simulation, lost frames of the MD simulation, and idle time of the analysis. We measure these metrics for a diverse set of molecular systems and characterize their trends for in situ and in transit configurations. We then model which frames are dropped and which ones are analyzed for a real use case. The insights gained from this study are generally applicable for in situ and in transit workflows that require optimization of parameters to minimize loss in workflow performance and analytic accuracy.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Molecular Dynamics (MD) simulations executed on state-of-the-art supercomputers are producing data at rates faster than it can be written out to disk. In situ and in transit analysis of data generated by MD simulations reduce the original volume of information by several orders of magnitude, thereby alleviating the negative impact of I/O bottlenecks. This work focuses on characterizing the impact of in situ and in transit analytics on the overall MD workflow performance, and the capability for capturing rapid, rare events in the simulated molecular system. The MD simulation and analysis processes share data via remote direct memory access (RDMA) using DataSpaces. Our metrics of interest are time spent waiting in I/O by the MD simulation, lost frames of the MD simulation, and idle time of the analysis. We measure these metrics for a diverse set of molecular systems and characterize their trends for in situ and in transit configurations. We then model which frames are dropped and which ones are analyzed for a real use case. The insights gained from this study are generally applicable for in situ and in transit workflows that require optimization of parameters to minimize loss in workflow performance and analytic accuracy.",
"fno": "245100a188",
"keywords": [
"Molecular Dynamics Method",
"Parallel Machines",
"RDMA",
"Remote Direct Memory Access",
"MD Simulation Analysis Processes",
"I O Bottlenecks",
"In Transit Analytics",
"In Situ Analytics",
"Next Generation Supercomputers",
"Molecular Dynamics Simulations",
"Simulated Molecular System",
"Proteins",
"Measurement",
"Analytical Models",
"Solid Modeling",
"Predictive Models",
"Data Models",
"Supercomputers",
"Scientific Workflows Data Analytics Performance Workload Modeling Remote Direct Memory Access"
],
"authors": [
{
"affiliation": "The University of Tennessee",
"fullName": "Michela Taufer",
"givenName": "Michela",
"surname": "Taufer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Tennessee",
"fullName": "Stephen Thomas",
"givenName": "Stephen",
"surname": "Thomas",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Tennessee",
"fullName": "Michael Wyatt",
"givenName": "Michael",
"surname": "Wyatt",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California",
"fullName": "Tu Mai Anh Do",
"givenName": "Tu Mai",
"surname": "Anh Do",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California",
"fullName": "Loïc Pottier",
"givenName": "Loïc",
"surname": "Pottier",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California",
"fullName": "Rafael Ferreira da Silva",
"givenName": "Rafael Ferreira",
"surname": "da Silva",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cornell University",
"fullName": "Harel Weinstein",
"givenName": "Harel",
"surname": "Weinstein",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cornell University; Lausanne University Hospital",
"fullName": "Michel A. Cuendet",
"givenName": "Michel A.",
"surname": "Cuendet",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of New Mexico",
"fullName": "Trilce Estrada",
"givenName": "Trilce",
"surname": "Estrada",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California",
"fullName": "Ewa Deelman",
"givenName": "Ewa",
"surname": "Deelman",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "escience",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-09-01T00:00:00",
"pubType": "proceedings",
"pages": "188-198",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-2451-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "245100a178",
"articleId": "1ike4Z9WrLi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "245100a199",
"articleId": "1ike187q8oM",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sc/2012/0806/0/1000a089",
"title": "Combining in-situ and in-transit processing to enable extreme-scale scientific analysis",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2012/1000a089/12OmNAY79dw",
"parentPublication": {
"id": "proceedings/sc/2012/0806/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccgrid/2014/2784/0/2784a277",
"title": "A Flexible Framework for Asynchronous in Situ and in Transit Analytics for Scientific Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/ccgrid/2014/2784a277/12OmNAkniTJ",
"parentPublication": {
"id": "proceedings/ccgrid/2014/2784/0",
"title": "2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccbd/2015/8350/0/8350a097",
"title": "Modeling Parallel Molecular Simulations on Amazon EC2",
"doi": null,
"abstractUrl": "/proceedings-article/ccbd/2015/8350a097/12OmNx4gUj5",
"parentPublication": {
"id": "proceedings/ccbd/2015/8350/0",
"title": "2015 International Conference on Cloud Computing and Big Data (CCBD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipdpsw/2014/4116/0/4116a536",
"title": "Exploring Large Scale Receptor-Ligand Pairs in Molecular Docking Workflows in HPC Clouds",
"doi": null,
"abstractUrl": "/proceedings-article/ipdpsw/2014/4116a536/12OmNzUPpin",
"parentPublication": {
"id": "proceedings/ipdpsw/2014/4116/0",
"title": "2014 IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPSW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09765476",
"title": "A Hybrid In Situ Approach for Cost Efficient Image Database Generation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09765476/1CY3PmkyDMk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiswc/2022/8798/0/879800a065",
"title": "Characterizing Molecular Dynamics Simulation on Commodity Platforms",
"doi": null,
"abstractUrl": "/proceedings-article/iiswc/2022/879800a065/1J4CgdGq9vG",
"parentPublication": {
"id": "proceedings/iiswc/2022/8798/0",
"title": "2022 IEEE International Symposium on Workload Characterization (IISWC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2022/6124/0/612400a182",
"title": "SIM-SITU: A Framework for the Faithful Simulation of in situ Processing",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2022/612400a182/1J6hxD8UJYA",
"parentPublication": {
"id": "proceedings/e-science/2022/6124/0",
"title": "2022 IEEE 18th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/works/2022/5191/0/519100a043",
"title": "Co-scheduling Ensembles of In Situ Workflows",
"doi": null,
"abstractUrl": "/proceedings-article/works/2022/519100a043/1KckpDKCTJK",
"parentPublication": {
"id": "proceedings/works/2022/5191/0",
"title": "2022 IEEE/ACM Workshop on Workflows in Support of Large-Scale Science (WORKS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dl/2019/6011/0/08945122",
"title": "DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding",
"doi": null,
"abstractUrl": "/proceedings-article/dl/2019/08945122/1grNxhdN8Ry",
"parentPublication": {
"id": "proceedings/dl/2019/6011/0",
"title": "2019 IEEE/ACM Third Workshop on Deep Learning on Supercomputers (DLS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09006048",
"title": "Visual Analytics for Deep Embeddings of Large Scale Molecular Dynamics Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09006048/1hJsu4lY0PS",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNx6g6nT",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAlvHLd",
"doi": "10.1109/BIBM.2017.8217875",
"title": "Complementing single-cell RNA-seq using bulk transcriptional profiles",
"normalizedTitle": "Complementing single-cell RNA-seq using bulk transcriptional profiles",
"abstract": "While high-throughput single cell technologies enable in depth examination of specific cell subsets, these experiments lack the context of these subsets in other cell types and diseases. We compared novel dendritic and monocyte signatures from single cell RNAseq with bulk transcriptome of immune cells to show that the gene signatures for the novel cell subsets are also up-regulated in functionally related but non-parental cell populations. We extended utility of these signatures by demonstrating their consistent down-regulation in cancers, up-regulation in autoimmune diseases, and signature-specific effects in infections. We encourage other researchers to similarly complement their experiments and analyses using existing, publicly available datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "While high-throughput single cell technologies enable in depth examination of specific cell subsets, these experiments lack the context of these subsets in other cell types and diseases. We compared novel dendritic and monocyte signatures from single cell RNAseq with bulk transcriptome of immune cells to show that the gene signatures for the novel cell subsets are also up-regulated in functionally related but non-parental cell populations. We extended utility of these signatures by demonstrating their consistent down-regulation in cancers, up-regulation in autoimmune diseases, and signature-specific effects in infections. We encourage other researchers to similarly complement their experiments and analyses using existing, publicly available datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "While high-throughput single cell technologies enable in depth examination of specific cell subsets, these experiments lack the context of these subsets in other cell types and diseases. We compared novel dendritic and monocyte signatures from single cell RNAseq with bulk transcriptome of immune cells to show that the gene signatures for the novel cell subsets are also up-regulated in functionally related but non-parental cell populations. We extended utility of these signatures by demonstrating their consistent down-regulation in cancers, up-regulation in autoimmune diseases, and signature-specific effects in infections. We encourage other researchers to similarly complement their experiments and analyses using existing, publicly available datasets.",
"fno": "08217875",
"keywords": [
"Sociology",
"Statistics",
"Immune System",
"Gene Expression",
"Cancer",
"Databases"
],
"authors": [
{
"affiliation": null,
"fullName": "Winston A. Haynes",
"givenName": "Winston A.",
"surname": "Haynes",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Francesco Vallania",
"givenName": "Francesco",
"surname": "Vallania",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Purvesh Khatri",
"givenName": "Purvesh",
"surname": "Khatri",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-11-01T00:00:00",
"pubType": "proceedings",
"pages": "1446-1450",
"year": "2017",
"issn": null,
"isbn": "978-1-5090-3050-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08217874",
"articleId": "12OmNrNh0Dx",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08217876",
"articleId": "12OmNwpGgOc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/itme/2015/8302/0/8302a117",
"title": "Identification of Potential Non-invasive Biomarkers for Breast Cancer Prognosis and Treatment by Systematic Bioinformatics Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2015/8302a117/12OmNCgJe36",
"parentPublication": {
"id": "proceedings/itme/2015/8302/0",
"title": "2015 7th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2013/1309/0/06732489",
"title": "Modeling competing endogenous RNA regulatory networks in glioblastoma multiforme",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2013/06732489/12OmNyaXPQp",
"parentPublication": {
"id": "proceedings/bibm/2013/1309/0",
"title": "2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2011/1799/0/06120474",
"title": "Identification of Breast Cancer Gene Signature in Protein Interaction Network Using Graph Centrality",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2011/06120474/12OmNybfrai",
"parentPublication": {
"id": "proceedings/bibm/2011/1799/0",
"title": "2011 IEEE International Conference on Bioinformatics and Biomedicine",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2018/6217/0/247100a251",
"title": "Quantitative Analysis of ECI2 Expression from RNA-Seq for Breast Cancer Gene Signatures",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2018/247100a251/17D45WrVggI",
"parentPublication": {
"id": "proceedings/bibe/2018/6217/0",
"title": "2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2018/6217/0/247100a273",
"title": "Identification of Potential Long Non-coding RNA Biomarkers for Breast Cancer Patients with Somatic BRCA1 Mutations from RNA-Seq Datasets",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2018/247100a273/17D45XERmkO",
"parentPublication": {
"id": "proceedings/bibe/2018/6217/0",
"title": "2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2018/6217/0/247100a323",
"title": "The Role of mRNA Transporter in Human Cancer",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2018/247100a323/17D45XeKgyp",
"parentPublication": {
"id": "proceedings/bibe/2018/6217/0",
"title": "2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/06/08985318",
"title": "Evolving Transcriptomic Profiles From Single-Cell RNA-Seq Data Using Nature-Inspired Multiobjective Optimization",
"doi": null,
"abstractUrl": "/journal/tb/2021/06/08985318/1hcy88sEadO",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313378",
"title": "Unsupervised Identification of SARS-CoV-2 Target Cell Groups via Nonlinear Dimensionality Reduction on Single-cell RNA-Seq Data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313378/1qmfY23X7Gw",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/04/09363460",
"title": "TiC2D: Trajectory Inference From Single-Cell RNA-Seq Data Using Consensus Clustering",
"doi": null,
"abstractUrl": "/journal/tb/2022/04/09363460/1rvy9yuLw0o",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cscc/2020/6503/0/650300a096",
"title": "Structural changes in transcriptional regulatory networks for cell-type-specific gene expression during hematopoiesis",
"doi": null,
"abstractUrl": "/proceedings-article/cscc/2020/650300a096/1t2mVF6spsQ",
"parentPublication": {
"id": "proceedings/cscc/2020/6503/0",
"title": "2020 24th International Conference on Circuits, Systems, Communications and Computers (CSCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNC3Xhhz",
"title": "2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)",
"acronym": "iccabs",
"groupId": "1800307",
"volume": "0",
"displayVolume": "0",
"year": "2013",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBKEyv5",
"doi": "10.1109/ICCABS.2013.6629234",
"title": "Towards whole transcriptome deconvolution using single-cell data",
"normalizedTitle": "Towards whole transcriptome deconvolution using single-cell data",
"abstract": "Obtaining whole-transcriptome expression profiles of closely related cell types is a daunting task faced by stem-cell biologists. Here we present an approach that utilizes single-cell qPCR probing of a small number of genes to aid in the deconvolution of whole-transcriptome profiles of mixed samples.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Obtaining whole-transcriptome expression profiles of closely related cell types is a daunting task faced by stem-cell biologists. Here we present an approach that utilizes single-cell qPCR probing of a small number of genes to aid in the deconvolution of whole-transcriptome profiles of mixed samples.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Obtaining whole-transcriptome expression profiles of closely related cell types is a daunting task faced by stem-cell biologists. Here we present an approach that utilizes single-cell qPCR probing of a small number of genes to aid in the deconvolution of whole-transcriptome profiles of mixed samples.",
"fno": "06629234",
"keywords": [
"Educational Institutions",
"Gene Expression",
"Deconvolution",
"Computer Science",
"Biological Cells",
"Computational Modeling"
],
"authors": [
{
"affiliation": "Comput. Sci. & Eng., Univ. of Connecticut, Storrs, CT, USA",
"fullName": "James Lindsay",
"givenName": "James",
"surname": "Lindsay",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Mol. & Cell Biol., Univ. of Connecticut, Storrs, CT, USA",
"fullName": "Craig E. Nelson",
"givenName": "Craig E.",
"surname": "Nelson",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Comput. Sci. & Eng., Univ. of Connecticut, Storrs, CT, USA",
"fullName": "Ion I. Mandoiu",
"givenName": "Ion I.",
"surname": "Mandoiu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccabs",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2013-06-01T00:00:00",
"pubType": "proceedings",
"pages": "1-1",
"year": "2013",
"issn": null,
"isbn": "978-1-4799-0716-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06629233",
"articleId": "12OmNwBBq96",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06629235",
"articleId": "12OmNxaw5cz",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2017/3050/0/08217875",
"title": "Complementing single-cell RNA-seq using bulk transcriptional profiles",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217875/12OmNAlvHLd",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccabs/2018/8520/0/08542078",
"title": "Tumor Copy Number Data Deconvolution Integrating Bulk and Single-cell Sequencing Data",
"doi": null,
"abstractUrl": "/proceedings-article/iccabs/2018/08542078/17D45VtKivv",
"parentPublication": {
"id": "proceedings/iccabs/2018/8520/0",
"title": "2018 IEEE 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669678",
"title": "Applications of single cell profiles of PBMC:Improvements of cell type classification",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669678/1A9W40WIuWY",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigdataservice/2019/0059/0/005900a301",
"title": "The Tumor Infiltrating Leukocyte Cell Composition Are Significant Markers for Prognostics of Radiotherapy of Rectal Cancer as Revealed by Cell Type Deconvolution",
"doi": null,
"abstractUrl": "/proceedings-article/bigdataservice/2019/005900a301/1dDLXXEFQFG",
"parentPublication": {
"id": "proceedings/bigdataservice/2019/0059/0",
"title": "2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/06/08985318",
"title": "Evolving Transcriptomic Profiles From Single-Cell RNA-Seq Data Using Nature-Inspired Multiobjective Optimization",
"doi": null,
"abstractUrl": "/journal/tb/2021/06/08985318/1hcy88sEadO",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2019/1867/0/08983394",
"title": "Single-cell Transcriptome Analysis of Mouse Leukocytes in Inflammatory Stimulation",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2019/08983394/1hguhUirTj2",
"parentPublication": {
"id": "proceedings/bibm/2019/1867/0",
"title": "2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313213",
"title": "Single-cell mRNA Profiles in PBMC",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313213/1qmfWB9fqxy",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313510",
"title": "Automation of Gene Expression Profile Analysis in Single Cell Data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313510/1qmghNWn7Zm",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/04/09363460",
"title": "TiC2D: Trajectory Inference From Single-Cell RNA-Seq Data Using Consensus Clustering",
"doi": null,
"abstractUrl": "/journal/tb/2022/04/09363460/1rvy9yuLw0o",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2020/2314/0/231400b672",
"title": "Methods of Identifying Cell Type from Single Cell RNA-seq Data and the Interpretation",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2020/231400b672/1tzyXpS6CiY",
"parentPublication": {
"id": "proceedings/icmcce/2020/2314/0",
"title": "2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAYXWAH",
"title": "2016 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII)",
"acronym": "iciicii",
"groupId": "1811364",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNxVV5WA",
"doi": "10.1109/ICIICII.2016.0083",
"title": "Parameter Extraction for Single-Diode Model of Solar Cell",
"normalizedTitle": "Parameter Extraction for Single-Diode Model of Solar Cell",
"abstract": "A method to extract five parameters in the single-diode equivalent circuit of a solar cell is described in detail. The parameter extraction is mainly from the knowledge of the sole information contained in the datasheets given by the manufacturer of the solar cell. Besides the information with regard to the most representative points of the I-V curve (short circuit, open circuit, and the maximum power point) provided by all manufacturers, it just needs one more operating point. The extra information can be obtained either from the datasheet or by simple testing without setting up a complicated measurement system. There is only one unknown parameter in the proposed objective function, reducing the dimension and complexity of heuristic algorithm. The algorithm is applied to extract five parameters in the equivalent circuit and fit the I-V curve of AzurSpace's solar cell 3C40. Experimental results show that this approach leads to a reduction of the measurement effort and allows an accurate reconstruction of the solar cell characteristics as well.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A method to extract five parameters in the single-diode equivalent circuit of a solar cell is described in detail. The parameter extraction is mainly from the knowledge of the sole information contained in the datasheets given by the manufacturer of the solar cell. Besides the information with regard to the most representative points of the I-V curve (short circuit, open circuit, and the maximum power point) provided by all manufacturers, it just needs one more operating point. The extra information can be obtained either from the datasheet or by simple testing without setting up a complicated measurement system. There is only one unknown parameter in the proposed objective function, reducing the dimension and complexity of heuristic algorithm. The algorithm is applied to extract five parameters in the equivalent circuit and fit the I-V curve of AzurSpace's solar cell 3C40. Experimental results show that this approach leads to a reduction of the measurement effort and allows an accurate reconstruction of the solar cell characteristics as well.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A method to extract five parameters in the single-diode equivalent circuit of a solar cell is described in detail. The parameter extraction is mainly from the knowledge of the sole information contained in the datasheets given by the manufacturer of the solar cell. Besides the information with regard to the most representative points of the I-V curve (short circuit, open circuit, and the maximum power point) provided by all manufacturers, it just needs one more operating point. The extra information can be obtained either from the datasheet or by simple testing without setting up a complicated measurement system. There is only one unknown parameter in the proposed objective function, reducing the dimension and complexity of heuristic algorithm. The algorithm is applied to extract five parameters in the equivalent circuit and fit the I-V curve of AzurSpace's solar cell 3C40. Experimental results show that this approach leads to a reduction of the measurement effort and allows an accurate reconstruction of the solar cell characteristics as well.",
"fno": "3575a319",
"keywords": [
"Photovoltaic Cells",
"Sociology",
"Statistics",
"Mathematical Model",
"Integrated Circuit Modeling",
"Equivalent Circuits",
"Photovoltaic Systems",
"Single Diode Model",
"Solar Cell",
"Parameter Extraction"
],
"authors": [
{
"affiliation": null,
"fullName": "R. Tai",
"givenName": "R.",
"surname": "Tai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "B. Y. Chen",
"givenName": "B. Y.",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "F. X. Chen",
"givenName": "F. X.",
"surname": "Chen",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iciicii",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-12-01T00:00:00",
"pubType": "proceedings",
"pages": "319-322",
"year": "2016",
"issn": null,
"isbn": "978-1-5090-3575-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3575a315",
"articleId": "12OmNwHQBf9",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3575a323",
"articleId": "12OmNvo67Es",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iciev/2013/0400/0/06572562",
"title": "Efficiency enhancement of InGaN based quantum well and quantum dot solar cell",
"doi": null,
"abstractUrl": "/proceedings-article/iciev/2013/06572562/12OmNBRKwBG",
"parentPublication": {
"id": "proceedings/iciev/2013/0400/0",
"title": "2013 2nd International Conference on Informatics, Electronics and Vision (ICIEV 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mcsi/2015/8673/0/8673a007",
"title": "Identification of Solar Cell Parameters with Firefly Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/mcsi/2015/8673a007/12OmNCd2rsF",
"parentPublication": {
"id": "proceedings/mcsi/2015/8673/0",
"title": "2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciev/2016/1269/0/07760148",
"title": "Comparison of theoretical efficiencies of three and four layer multijunction solar cell and the effects of varying the bottom layer material",
"doi": null,
"abstractUrl": "/proceedings-article/iciev/2016/07760148/12OmNwIpNoW",
"parentPublication": {
"id": "proceedings/iciev/2016/1269/0",
"title": "2016 International Conference on Informatics, Electronics and Vision (ICIEV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dft/2010/8447/0/05634902",
"title": "Time/Temperature Degradation of Solar Cells under the Single Diode Model",
"doi": null,
"abstractUrl": "/proceedings-article/dft/2010/05634902/12OmNyv7mks",
"parentPublication": {
"id": "proceedings/dft/2010/8447/0",
"title": "2010 IEEE 25th International Symposium on Defect and Fault Tolerance in VLSI Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ghtc/2011/4595/0/06103604",
"title": "An Efficient Design of Solar Cell Antenna for Mobile and Vehicular Applications",
"doi": null,
"abstractUrl": "/proceedings-article/ghtc/2011/06103604/12OmNzahbUm",
"parentPublication": {
"id": "proceedings/ghtc/2011/4595/0",
"title": "IEEE Global Humanitarian Technology Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iceitsa/2022/6401/0/640100a015",
"title": "Research on Modeling and Simulation of Cd-Te Thin Film Solar Photovoltaic Cells",
"doi": null,
"abstractUrl": "/proceedings-article/iceitsa/2022/640100a015/1L086eEvOAU",
"parentPublication": {
"id": "proceedings/iceitsa/2022/6401/0",
"title": "2022 2nd International Conference on Electronic Information Technology and Smart Agriculture (ICEITSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icftic/2022/2195/0/10075205",
"title": "A hybrid algorithmic method for evaluating the solar cell model parameters",
"doi": null,
"abstractUrl": "/proceedings-article/icftic/2022/10075205/1LRl3tGsE00",
"parentPublication": {
"id": "proceedings/icftic/2022/2195/0",
"title": "2022 4th International Conference on Frontiers Technology of Information and Computer (ICFTIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icapc/2022/6303/0/630300a026",
"title": "Characteristics analysis and development trend overview of solar cells",
"doi": null,
"abstractUrl": "/proceedings-article/icapc/2022/630300a026/1M7KYUdKQo0",
"parentPublication": {
"id": "proceedings/icapc/2022/6303/0",
"title": "2022 International Conference on Applied Physics and Computing (ICAPC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iceee/2019/3910/0/391000a065",
"title": "Comparative Parameter Estimation of Single Diode PV-Cell Model by Using Sine-Cosine Algorithm and Whale Optimization Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/iceee/2019/391000a065/1cpqD8mTU76",
"parentPublication": {
"id": "proceedings/iceee/2019/3910/0",
"title": "2019 6th International Conference on Electrical and Electronics Engineering (ICEEE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isctis/2021/1441/0/144100a418",
"title": "Silicon-based solar cell: Materials, fabrication and applications",
"doi": null,
"abstractUrl": "/proceedings-article/isctis/2021/144100a418/1yEZBaBOTVm",
"parentPublication": {
"id": "proceedings/isctis/2021/1441/0",
"title": "2021 International Symposium on Computer Technology and Information Science (ISCTIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKirt",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45XDIXVR",
"doi": "10.1109/CVPR.2018.00970",
"title": "Weakly Supervised Learning of Single-Cell Feature Embeddings",
"normalizedTitle": "Weakly Supervised Learning of Single-Cell Feature Embeddings",
"abstract": "We study the problem of learning representations for single cells in microscopy images to discover biological relationships between their experimental conditions. Many new applications in drug discovery and functional genomics require capturing the morphology of individual cells as comprehensively as possible. Deep convolutional neural networks (CNNs) can learn powerful visual representations, but require ground truth for training; this is rarely available in biomedical profiling experiments. While we do not know which experimental treatments produce cells that look alike, we do know that cells exposed to the same experimental treatment should generally look similar. Thus, we explore training CNNs using a weakly supervised approach that uses this information for feature learning. In addition, the training stage is regularized to control for unwanted variations using mixup or RNNs. We conduct experiments on two different datasets; the proposed approach yields single-cell embeddings that are more accurate than the widely adopted classical features, and are competitive with previously proposed transfer learning approaches.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We study the problem of learning representations for single cells in microscopy images to discover biological relationships between their experimental conditions. Many new applications in drug discovery and functional genomics require capturing the morphology of individual cells as comprehensively as possible. Deep convolutional neural networks (CNNs) can learn powerful visual representations, but require ground truth for training; this is rarely available in biomedical profiling experiments. While we do not know which experimental treatments produce cells that look alike, we do know that cells exposed to the same experimental treatment should generally look similar. Thus, we explore training CNNs using a weakly supervised approach that uses this information for feature learning. In addition, the training stage is regularized to control for unwanted variations using mixup or RNNs. We conduct experiments on two different datasets; the proposed approach yields single-cell embeddings that are more accurate than the widely adopted classical features, and are competitive with previously proposed transfer learning approaches.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We study the problem of learning representations for single cells in microscopy images to discover biological relationships between their experimental conditions. Many new applications in drug discovery and functional genomics require capturing the morphology of individual cells as comprehensively as possible. Deep convolutional neural networks (CNNs) can learn powerful visual representations, but require ground truth for training; this is rarely available in biomedical profiling experiments. While we do not know which experimental treatments produce cells that look alike, we do know that cells exposed to the same experimental treatment should generally look similar. Thus, we explore training CNNs using a weakly supervised approach that uses this information for feature learning. In addition, the training stage is regularized to control for unwanted variations using mixup or RNNs. We conduct experiments on two different datasets; the proposed approach yields single-cell embeddings that are more accurate than the widely adopted classical features, and are competitive with previously proposed transfer learning approaches.",
"fno": "642000j309",
"keywords": [
"Biology Computing",
"Cellular Biophysics",
"Convolution",
"Feedforward Neural Nets",
"Genomics",
"Image Classification",
"Image Representation",
"Learning Artificial Intelligence",
"Recurrent Neural Nets",
"Convolutional Neural Networks",
"Ground Truth",
"Biomedical Profiling Experiments",
"Weakly Supervised Approach",
"Feature Learning",
"Training Stage",
"Single Cell Embeddings",
"Transfer Learning Approaches",
"Supervised Learning",
"Single Cell Feature Embeddings",
"Microscopy Images",
"Biological Relationships",
"Drug Discovery",
"Functional Genomics",
"Visual Representations",
"CNN Training",
"RNN",
"Compounds",
"Feature Extraction",
"Biology",
"Training",
"Sociology",
"Statistics",
"Microscopy"
],
"authors": [
{
"affiliation": null,
"fullName": "Juan C. Caicedo",
"givenName": "Juan C.",
"surname": "Caicedo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Claire McQuin",
"givenName": "Claire",
"surname": "McQuin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Allen Goodman",
"givenName": "Allen",
"surname": "Goodman",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Shantanu Singh",
"givenName": "Shantanu",
"surname": "Singh",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Anne E. Carpenter",
"givenName": "Anne E.",
"surname": "Carpenter",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-06-01T00:00:00",
"pubType": "proceedings",
"pages": "9309-9318",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-6420-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "642000j300",
"articleId": "17D45XeKgs1",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "642000j319",
"articleId": "17D45XeKgyj",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccvw/2017/1034/0/1034a049",
"title": "Discovery of Rare Phenotypes in Cellular Images Using Weakly Supervised Deep Learning",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2017/1034a049/12OmNAlvHK6",
"parentPublication": {
"id": "proceedings/iccvw/2017/1034/0",
"title": "2017 IEEE International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217875",
"title": "Complementing single-cell RNA-seq using bulk transcriptional profiles",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217875/12OmNAlvHLd",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08218022",
"title": "On the robustness of mixture model-based unsupervised learning in single-cell analyses",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08218022/12OmNzUPpic",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2017/04/07962189",
"title": "Mitosis Detection in Phase Contrast Microscopy Image Sequences of Stem Cell Populations: A Critical Review",
"doi": null,
"abstractUrl": "/journal/bd/2017/04/07962189/13rRUxBa5dP",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2018/05/08060531",
"title": "Cell Population Tracking in a Honeycomb Structure Using an IMM Filter Based 3D Local Graph Matching Model",
"doi": null,
"abstractUrl": "/journal/tb/2018/05/08060531/14dcDYMpxVZ",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903604",
"title": "Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903604/1GZomAOeEzS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2019/4604/0/460400a230",
"title": "Tabular Cell Classification Using Pre-Trained Cell Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2019/460400a230/1h5XORF1LTa",
"parentPublication": {
"id": "proceedings/icdm/2019/4604/0",
"title": "2019 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2020/9574/0/957400a616",
"title": "CNN Based iPS Cell Formation Stage Classifier for Human iPS Cell Growth Status Prediction Using Time-lapse Microscopy Images",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2020/957400a616/1pBMvR6x0Dm",
"parentPublication": {
"id": "proceedings/bibe/2020/9574/0",
"title": "2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313460",
"title": "Integration for single-cell RNA sequencing data based on the shared cell type assignment",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313460/1qmfOAmnOkU",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2021/4261/0/09635557",
"title": "Automatic Estimation of Limbal Stem Cell Densities in Cultured Epithelial Cell Microscopy Imaging",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2021/09635557/1zmvwXcs2Ry",
"parentPublication": {
"id": "proceedings/bibe/2021/4261/0",
"title": "2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JC1F8KcINO",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "9994793",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JC28ojFy2k",
"doi": "10.1109/BIBM55620.2022.9995189",
"title": "Single-cell TF-DNA binding prediction and analysis based on transfer learning framework",
"normalizedTitle": "Single-cell TF-DNA binding prediction and analysis based on transfer learning framework",
"abstract": "Cell type-specific gene expressions during development or in disease are regulated by interactions between transcription factors (TFs) and their binding sites. Recently, many deep learning approaches have been developed to characterize TF-DNA binding within a population of cells. However, determining TF binding sites (TFBSs) in single cells remains challenging due to the sparsity of data. Here, we propose a multi-stage transfer learning framework called STAPLE for single-cell TF-DNA binding prediction and analysis. Specifically, we design the Cell Type Learning to capture the relationship between different TF-DNA binding events in the same cell type. Meanwhile, we present Individual Learning to extract common motif and chromatin accessibility features of a particular binding event in a cellular population. In addition, we leverage Single-cell Learning to annotate TFBSs in each cell without any supervised label. Extensive experiments based on 570 single-cell datasets validate the effectiveness of our framework for considering cellular heterogeneity, outperforming current methods. This work can provide new insight into the relationship between TF-DNA binding and cellular heterogeneity. The source code of STAPLE can be found at https://github.com/ZhangLab312/STAPLE.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cell type-specific gene expressions during development or in disease are regulated by interactions between transcription factors (TFs) and their binding sites. Recently, many deep learning approaches have been developed to characterize TF-DNA binding within a population of cells. However, determining TF binding sites (TFBSs) in single cells remains challenging due to the sparsity of data. Here, we propose a multi-stage transfer learning framework called STAPLE for single-cell TF-DNA binding prediction and analysis. Specifically, we design the Cell Type Learning to capture the relationship between different TF-DNA binding events in the same cell type. Meanwhile, we present Individual Learning to extract common motif and chromatin accessibility features of a particular binding event in a cellular population. In addition, we leverage Single-cell Learning to annotate TFBSs in each cell without any supervised label. Extensive experiments based on 570 single-cell datasets validate the effectiveness of our framework for considering cellular heterogeneity, outperforming current methods. This work can provide new insight into the relationship between TF-DNA binding and cellular heterogeneity. The source code of STAPLE can be found at https://github.com/ZhangLab312/STAPLE.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cell type-specific gene expressions during development or in disease are regulated by interactions between transcription factors (TFs) and their binding sites. Recently, many deep learning approaches have been developed to characterize TF-DNA binding within a population of cells. However, determining TF binding sites (TFBSs) in single cells remains challenging due to the sparsity of data. Here, we propose a multi-stage transfer learning framework called STAPLE for single-cell TF-DNA binding prediction and analysis. Specifically, we design the Cell Type Learning to capture the relationship between different TF-DNA binding events in the same cell type. Meanwhile, we present Individual Learning to extract common motif and chromatin accessibility features of a particular binding event in a cellular population. In addition, we leverage Single-cell Learning to annotate TFBSs in each cell without any supervised label. Extensive experiments based on 570 single-cell datasets validate the effectiveness of our framework for considering cellular heterogeneity, outperforming current methods. This work can provide new insight into the relationship between TF-DNA binding and cellular heterogeneity. The source code of STAPLE can be found at https://github.com/ZhangLab312/STAPLE.",
"fno": "09995189",
"keywords": [
"Cellular Biophysics",
"Deep Learning Artificial Intelligence",
"Diseases",
"DNA",
"Genetics",
"Medical Computing",
"Molecular Biophysics",
"Proteins",
"Cell Type Learning",
"Cell Type Specific Gene Expressions",
"Cellular Heterogeneity",
"Cellular Population",
"Chromatin",
"Deep Learning",
"Disease",
"Single Cell TF DNA Binding Prediction",
"STAPLE",
"Transcription Factor Binding Sites",
"Transfer Learning Framework",
"Deep Learning",
"Source Coding",
"Sociology",
"Transfer Learning",
"Genomics",
"Feature Extraction",
"Software",
"TF DNA Binding",
"Single Cell",
"Transfer Learning"
],
"authors": [
{
"affiliation": "Chengdu University of Information Technology,School of Computer Science,Chengdu,China",
"fullName": "Zixuan Wang",
"givenName": "Zixuan",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chengdu University of Information Technology,School of Computer Science,Chengdu,China",
"fullName": "Yongqing Zhang",
"givenName": "Yongqing",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chengdu University of Information Technology,School of Computer Science,Chengdu,China",
"fullName": "Yun Yu",
"givenName": "Yun",
"surname": "Yu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chengdu University of Information Technology,School of Computer Science,Chengdu,China",
"fullName": "Maocheng Wang",
"givenName": "Maocheng",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chengdu University of Information Technology,School of Computer Science,Chengdu,China",
"fullName": "Yuhang Liu",
"givenName": "Yuhang",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Institute of Fundamental and Frontire Sciences University of Electronic Science and Technology of China,Chengdu,China",
"fullName": "Quan Zou",
"givenName": "Quan",
"surname": "Zou",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-12-01T00:00:00",
"pubType": "proceedings",
"pages": "589-594",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6819-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09995653",
"articleId": "1JC2Qlsd0Gs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09995710",
"articleId": "1JC1RCeQztK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2014/5669/0/06999140",
"title": "Discovering protein-DNA binding cores by aligned pattern clustering",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2014/06999140/12OmNBKW9HN",
"parentPublication": {
"id": "proceedings/bibm/2014/5669/0",
"title": "2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2012/4747/0/4747a965",
"title": "Predicting Approximate Protein-DNA Binding Cores Using Association Rule Mining",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2012/4747a965/12OmNrMZpln",
"parentPublication": {
"id": "proceedings/icde/2012/4747/0",
"title": "2012 IEEE 28th International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2008/3495/0/3495a709",
"title": "Ensemble Machine Methods for DNA Binding",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2008/3495a709/12OmNx38vWs",
"parentPublication": {
"id": "proceedings/icmla/2008/3495/0",
"title": "2008 Seventh International Conference on Machine Learning and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2001/1423/0/00974424",
"title": "Mining genome variation to associate disease with transcription factor binding site alteration",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2001/00974424/12OmNy49sSM",
"parentPublication": {
"id": "proceedings/bibe/2001/1423/0",
"title": "Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2015/01/06867331",
"title": "Discovering Binding Cores in Protein-DNA Binding Using Association Rule Mining with Statistical Measures",
"doi": null,
"abstractUrl": "/journal/tb/2015/01/06867331/13rRUIJcWka",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2018/05/08107554",
"title": "Sequence-Based Prediction of Putative Transcription Factor Binding Sites in DNA Sequences of Any Length",
"doi": null,
"abstractUrl": "/journal/tb/2018/05/08107554/14dcDYx5cUp",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669594",
"title": "DeepBSI: a multimodal deep learning framework for predicting the transcription factor binding site and intensity",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669594/1A9VqkbP6Cs",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995698",
"title": "Predicting cell type-specific effects of variants on TF-DNA binding by meta-learning",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995698/1JC2F48gujK",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2020/6034/0/603400a350",
"title": "Identifying Cell Type Specific TF Combinatorial Regulation via a Two-Stage Statistical Method",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2020/603400a350/1jdDuFixrDG",
"parentPublication": {
"id": "proceedings/bigcomp/2020/6034/0",
"title": "2020 IEEE International Conference on Big Data and Smart Computing (BigComp)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/02/09206088",
"title": "Learning Useful Representations of DNA Sequences From ChIP-Seq Datasets for Exploring Transcription Factor Binding Specificities",
"doi": null,
"abstractUrl": "/journal/tb/2022/02/09206088/1npxykVK0us",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JC1F8KcINO",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "9994793",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JC3dxJYGIw",
"doi": "10.1109/BIBM55620.2022.9995220",
"title": "scARMF: Association Rule Mining-based feature selection Framework for Single-Cell transcriptomics data",
"normalizedTitle": "scARMF: Association Rule Mining-based feature selection Framework for Single-Cell transcriptomics data",
"abstract": "Single-cell RNA-sequencing (scRNA-seq) technologies have allowed researchers to investigate transcriptional regulation at a cellular resolution. One such analysis often involves extracting statistically significant groups of cells identified as clusters that enable cell-type identification, based on the presence or absence of canonical markers. However, it has been observed that cells with similar gene expression profiles, m ay sometimes represent variable transcriptional states. Identifying cell-type specific markers, is hence, not sufficient enough to understand the underlying molecular activity within a particular cell cluster. Rather, we should focus on finding key regulators within cell clusters. In order to assess cells’ functionality beyond marker-based studies, genes driving or being driven by these key regulators need to be analysed against reference databases. In this work, we have developed an Association Rule Mining (ARM)-based feature selection Framework, called scARMF, which can identify major gene-gene interactions within a specific cell-cluster of interest in scRNA-seq data. These interaction networks have helped us identify key regulatory hubs (genes), some of which have been found to be relevant canonical markers when validated against a benchmarked reference database. The sub-networks formed by hub genes along with their neighbours, have been further assessed via Over Representation Analysis (ORA)-based pathway enrichment. This has revealed interesting functional characteristics that can be important for further downstream biological interpretations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Single-cell RNA-sequencing (scRNA-seq) technologies have allowed researchers to investigate transcriptional regulation at a cellular resolution. One such analysis often involves extracting statistically significant groups of cells identified as clusters that enable cell-type identification, based on the presence or absence of canonical markers. However, it has been observed that cells with similar gene expression profiles, m ay sometimes represent variable transcriptional states. Identifying cell-type specific markers, is hence, not sufficient enough to understand the underlying molecular activity within a particular cell cluster. Rather, we should focus on finding key regulators within cell clusters. In order to assess cells’ functionality beyond marker-based studies, genes driving or being driven by these key regulators need to be analysed against reference databases. In this work, we have developed an Association Rule Mining (ARM)-based feature selection Framework, called scARMF, which can identify major gene-gene interactions within a specific cell-cluster of interest in scRNA-seq data. These interaction networks have helped us identify key regulatory hubs (genes), some of which have been found to be relevant canonical markers when validated against a benchmarked reference database. The sub-networks formed by hub genes along with their neighbours, have been further assessed via Over Representation Analysis (ORA)-based pathway enrichment. This has revealed interesting functional characteristics that can be important for further downstream biological interpretations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Single-cell RNA-sequencing (scRNA-seq) technologies have allowed researchers to investigate transcriptional regulation at a cellular resolution. One such analysis often involves extracting statistically significant groups of cells identified as clusters that enable cell-type identification, based on the presence or absence of canonical markers. However, it has been observed that cells with similar gene expression profiles, m ay sometimes represent variable transcriptional states. Identifying cell-type specific markers, is hence, not sufficient enough to understand the underlying molecular activity within a particular cell cluster. Rather, we should focus on finding key regulators within cell clusters. In order to assess cells’ functionality beyond marker-based studies, genes driving or being driven by these key regulators need to be analysed against reference databases. In this work, we have developed an Association Rule Mining (ARM)-based feature selection Framework, called scARMF, which can identify major gene-gene interactions within a specific cell-cluster of interest in scRNA-seq data. These interaction networks have helped us identify key regulatory hubs (genes), some of which have been found to be relevant canonical markers when validated against a benchmarked reference database. The sub-networks formed by hub genes along with their neighbours, have been further assessed via Over Representation Analysis (ORA)-based pathway enrichment. This has revealed interesting functional characteristics that can be important for further downstream biological interpretations.",
"fno": "09995220",
"keywords": [
"Biology Computing",
"Cellular Biophysics",
"Data Mining",
"Genetics",
"Genomics",
"Molecular Biophysics",
"Molecular Clusters",
"Molecular Configurations",
"RNA",
"Association Rule Mining Based Feature Selection Framework",
"Benchmarked Reference Database",
"Canonical Markers",
"Cell Clusters",
"Cell Type Identification",
"Cell Type Specific Markers",
"Gene Expression Profiles",
"Gene Gene Interactions",
"Hub Genes",
"Key Regulators",
"Key Regulatory Hubs",
"Marker Based Studies",
"Over Representation Analysis Based Pathway Enrichment",
"Sc ARMF",
"Sc RNA Seq Data",
"Single Cell RNA Sequencing",
"Single Cell Transcriptomics Data",
"Statistically Significant Groups",
"Transcriptional Regulation",
"Variable Transcriptional States",
"Regulators",
"Databases",
"Buildings",
"Cells Biology",
"Benchmark Testing",
"Feature Extraction",
"Regulation",
"Sc RNA Seq",
"Association Rule Mining",
"Gene Gene Interaction",
"Pathway Enrichment Analysis"
],
"authors": [
{
"affiliation": "University of Calcutta,A. K. Choudhury School of Information Technology,Kolkata,India",
"fullName": "Dibyendu Bikash Seal",
"givenName": "Dibyendu Bikash",
"surname": "Seal",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bioinformatics and Data Mining Novo Nordisk A/S,Malov,Denmark",
"fullName": "Vivek Das",
"givenName": "Vivek",
"surname": "Das",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Indian Statistical Institute,Machine Intelligence Unit,Kolkata,India",
"fullName": "Rajat K. De",
"givenName": "Rajat K.",
"surname": "De",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-12-01T00:00:00",
"pubType": "proceedings",
"pages": "3144-3151",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6819-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09995100",
"articleId": "1JC1Ptoi69G",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09995294",
"articleId": "1JC2XrTpHX2",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "trans/tb/2020/02/08388285",
"title": "Comparison of Computational Methods for Imputing Single-Cell RNA-Sequencing Data",
"doi": null,
"abstractUrl": "/journal/tb/2020/02/08388285/13rRUB7a1en",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccabs/2018/8520/0/08541950",
"title": "Computational cell cycle analysis of single cell RNA-seq data",
"doi": null,
"abstractUrl": "/proceedings-article/iccabs/2018/08541950/17D45VsBU2r",
"parentPublication": {
"id": "proceedings/iccabs/2018/8520/0",
"title": "2018 IEEE 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669826",
"title": "PBMC Cell Classification from Single Cell mRNA Expression by Artificial Neural Networks, Profiles, Gene Markers, and Protein Markers",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669826/1A9VsbLYere",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995574",
"title": "A Single-Cell-Resolution Quantitative Metric of Similarity to a Target Cell Type for scRNA-seq Data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995574/1JC2sJaIW64",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995223",
"title": "BayesImpute: a Bayesian imputation method for single-cell RNA-seq data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995223/1JC34ESwNdS",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313569",
"title": "Accurately Clustering Single-cell RNA-seq data by Capturing Structural Relations between Cells through Graph Convolutional Network",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313569/1qmg2wG65oI",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313483",
"title": "A data denoising approach to optimize functional clustering of single cell RNA-sequencing data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313483/1qmg3SpLsqI",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313478",
"title": "A robust single cell clustering method based on subspace learning and partial imputation",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313478/1qmgf5LBL1u",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cscc/2020/6503/0/650300a096",
"title": "Structural changes in transcriptional regulatory networks for cell-type-specific gene expression during hematopoiesis",
"doi": null,
"abstractUrl": "/proceedings-article/cscc/2020/650300a096/1t2mVF6spsQ",
"parentPublication": {
"id": "proceedings/cscc/2020/6503/0",
"title": "2020 24th International Conference on Circuits, Systems, Communications and Computers (CSCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2020/2314/0/231400b672",
"title": "Methods of Identifying Cell Type from Single Cell RNA-seq Data and the Interpretation",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2020/231400b672/1tzyXpS6CiY",
"parentPublication": {
"id": "proceedings/icmcce/2020/2314/0",
"title": "2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1qmfHK8AjMQ",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1qmfOAmnOkU",
"doi": "10.1109/BIBM49941.2020.9313460",
"title": "Integration for single-cell RNA sequencing data based on the shared cell type assignment",
"normalizedTitle": "Integration for single-cell RNA sequencing data based on the shared cell type assignment",
"abstract": "At present, many single-cell experiments from different laboratories and different sequencing platforms generate a large amount of RNA sequencing data, which is convenient for the research of new cell types detecting, cell clustering, gene regulatory network constructing and other downstream analysis. However, data from different laboratories or different sequencing platforms will contain batch effects that may compromise the integration and interpretation of the data. Existing methods don't achieve satisfactory integration results when the cell type composition varies greatly between batches. In this paper, we propose a novel method based on utilizing biological prior knowledge to guide the correction, which effectively solves the above problems and also outperforms other algorithms when similar cell types exist among batches or quantity distribution of cells from various cell types is seriously unbalanced.",
"abstracts": [
{
"abstractType": "Regular",
"content": "At present, many single-cell experiments from different laboratories and different sequencing platforms generate a large amount of RNA sequencing data, which is convenient for the research of new cell types detecting, cell clustering, gene regulatory network constructing and other downstream analysis. However, data from different laboratories or different sequencing platforms will contain batch effects that may compromise the integration and interpretation of the data. Existing methods don't achieve satisfactory integration results when the cell type composition varies greatly between batches. In this paper, we propose a novel method based on utilizing biological prior knowledge to guide the correction, which effectively solves the above problems and also outperforms other algorithms when similar cell types exist among batches or quantity distribution of cells from various cell types is seriously unbalanced.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "At present, many single-cell experiments from different laboratories and different sequencing platforms generate a large amount of RNA sequencing data, which is convenient for the research of new cell types detecting, cell clustering, gene regulatory network constructing and other downstream analysis. However, data from different laboratories or different sequencing platforms will contain batch effects that may compromise the integration and interpretation of the data. Existing methods don't achieve satisfactory integration results when the cell type composition varies greatly between batches. In this paper, we propose a novel method based on utilizing biological prior knowledge to guide the correction, which effectively solves the above problems and also outperforms other algorithms when similar cell types exist among batches or quantity distribution of cells from various cell types is seriously unbalanced.",
"fno": "09313460",
"keywords": [
"Biological Techniques",
"Biology Computing",
"Cellular Biophysics",
"Genetics",
"Genomics",
"Molecular Biophysics",
"RNA",
"Single Cell RNA Sequencing Data",
"Shared Cell Type Assignment",
"Cell Clustering",
"Gene Regulatory Network",
"Sequential Analysis",
"Biology",
"Sociology",
"RNA",
"Measurement",
"Data Visualization",
"Manifolds",
"Data Integration",
"Batch Effect",
"The Shared Cell Type",
"Supervised Cell Type Assignment"
],
"authors": [
{
"affiliation": "Fudan University,Shanghai Key Lab of Intelligent Information Processing School of Computer Science and Technology,Shanghai,China",
"fullName": "Yin Zhang",
"givenName": "Yin",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Fudan University,Shanghai Key Lab of Intelligent Information Processing School of Computer Science and Technology,Shanghai,China",
"fullName": "Fei Wang",
"givenName": "Fei",
"surname": "Wang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-12-01T00:00:00",
"pubType": "proceedings",
"pages": "232-235",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6215-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09313318",
"articleId": "1qmgcf22uOY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09313425",
"articleId": "1qmg8yNYIGQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2017/3050/0/08217650",
"title": "Differential gene expression analysis in single-cell RNA sequencing data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217650/12OmNAkWvHu",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2020/02/08388285",
"title": "Comparison of Computational Methods for Imputing Single-Cell RNA-Sequencing Data",
"doi": null,
"abstractUrl": "/journal/tb/2020/02/08388285/13rRUB7a1en",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669638",
"title": "DeepCI: a deep learning based clustering method for single cell RNA-seq data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669638/1A9Vmi0p8EU",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669529",
"title": "Single-cell RNA sequencing data clustering using graph convolutional networks",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669529/1A9VphHKZxK",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669148",
"title": "Cell type identification for single cell RNA data by bulk data reference projection",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669148/1A9WoQX6C1G",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisai/2021/0692/0/069200a797",
"title": "Clustering single-cell RNA sequencing data by multi-view latent embedding learning",
"doi": null,
"abstractUrl": "/proceedings-article/cisai/2021/069200a797/1BmO5OAo69W",
"parentPublication": {
"id": "proceedings/cisai/2021/0692/0",
"title": "2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2021/5841/0/584100a344",
"title": "Missing Value Recovery for Single Cell RNA Sequencing Data",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2021/584100a344/1EpL8APQKju",
"parentPublication": {
"id": "proceedings/csci/2021/5841/0",
"title": "2021 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995574",
"title": "A Single-Cell-Resolution Quantitative Metric of Similarity to a Target Cell Type for scRNA-seq Data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995574/1JC2sJaIW64",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995011",
"title": "Analyses of cell-to-cell communication combining a heterogeneous deep ensemble framework and scoring approaches from single-cell RNA sequencing data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995011/1JC3reRAj4c",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2020/05/08673591",
"title": "Single-Cell RNA Sequencing Data Interpretation by Evolutionary Multiobjective Clustering",
"doi": null,
"abstractUrl": "/journal/tb/2020/05/08673591/1nJspSt0kTe",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1zmvjlvd5Ek",
"title": "2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)",
"acronym": "bibe",
"groupId": "1000075",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1zmvwXcs2Ry",
"doi": "10.1109/BIBE52308.2021.9635557",
"title": "Automatic Estimation of Limbal Stem Cell Densities in Cultured Epithelial Cell Microscopy Imaging",
"normalizedTitle": "Automatic Estimation of Limbal Stem Cell Densities in Cultured Epithelial Cell Microscopy Imaging",
"abstract": "Limbal stem cell deficiency (LSCD) is a progressive corneal disease that renders the corneal epithelium unable to repair itself, which can lead to the eventual loss of vision. Advances in technology have allowed for the growth of limbal stem cells ex-vivo for the purposes of transplantation. One method used to evaluate the quality of these cultivated cells is cell density, which is typically calculated manually by experts, which is time-consuming and has high inter-rater variability. The goal of this project was to create a tool that automatically calculates cell density from digital images of the cultured cells. Results were compared against annotations from four experts with varying levels of experience. Cell counts had high correlation with expert annotations (r=0.64, p<0.01). When compared to human annotators with lower clinical experience, the algorithm achieved significantly better agreement with highly experienced annotators (r=0.75 vs r=0.19, p<0.01). These results suggest that the automated tool can provide meaningful cell density counts, which can potentially improve annotation consistency and reduce time required for evaluating LSCD cell cultures.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Limbal stem cell deficiency (LSCD) is a progressive corneal disease that renders the corneal epithelium unable to repair itself, which can lead to the eventual loss of vision. Advances in technology have allowed for the growth of limbal stem cells ex-vivo for the purposes of transplantation. One method used to evaluate the quality of these cultivated cells is cell density, which is typically calculated manually by experts, which is time-consuming and has high inter-rater variability. The goal of this project was to create a tool that automatically calculates cell density from digital images of the cultured cells. Results were compared against annotations from four experts with varying levels of experience. Cell counts had high correlation with expert annotations (r=0.64, p<0.01). When compared to human annotators with lower clinical experience, the algorithm achieved significantly better agreement with highly experienced annotators (r=0.75 vs r=0.19, p<0.01). These results suggest that the automated tool can provide meaningful cell density counts, which can potentially improve annotation consistency and reduce time required for evaluating LSCD cell cultures.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Limbal stem cell deficiency (LSCD) is a progressive corneal disease that renders the corneal epithelium unable to repair itself, which can lead to the eventual loss of vision. Advances in technology have allowed for the growth of limbal stem cells ex-vivo for the purposes of transplantation. One method used to evaluate the quality of these cultivated cells is cell density, which is typically calculated manually by experts, which is time-consuming and has high inter-rater variability. The goal of this project was to create a tool that automatically calculates cell density from digital images of the cultured cells. Results were compared against annotations from four experts with varying levels of experience. Cell counts had high correlation with expert annotations (r=0.64, p<0.01). When compared to human annotators with lower clinical experience, the algorithm achieved significantly better agreement with highly experienced annotators (r=0.75 vs r=0.19, p<0.01). These results suggest that the automated tool can provide meaningful cell density counts, which can potentially improve annotation consistency and reduce time required for evaluating LSCD cell cultures.",
"fno": "09635557",
"keywords": [
"Biomedical Optical Imaging",
"Cellular Biophysics",
"Diseases",
"Eye",
"Medical Image Processing",
"Vision",
"Automatic Estimation",
"Limbal Stem Cell Densities",
"Cultured Epithelial Cell Microscopy",
"Limbal Stem Cell Deficiency",
"Progressive Corneal Disease",
"Corneal Epithelium",
"Limbal Stem Cells Ex Vivo",
"Cultivated Cells",
"High Inter Rater Variability",
"Automatically Calculates Cell Density",
"Digital Images",
"Cultured Cells",
"Cell Counts",
"Expert Annotations",
"Human Annotators",
"Highly Experienced Annotators",
"Meaningful Cell Density",
"LSCD Cell Cultures",
"Machine Learning Algorithms",
"Annotations",
"Microscopy",
"Estimation",
"Cells Biology",
"Stem Cells",
"Manuals",
"Limbal Stem Cell Deficiency",
"Medical Image Analysis",
"Cell Density Estimation",
"Image J"
],
"authors": [
{
"affiliation": "University of California,Medical Informatics,Los Angeles,CA,USA",
"fullName": "Nathan Siu",
"givenName": "Nathan",
"surname": "Siu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Stein Eye Institute University of California,Los Angeles,CA,USA",
"fullName": "Maxime Ruiz",
"givenName": "Maxime",
"surname": "Ruiz",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Stein Eye Institute University of California,Los Angeles,CA,USA",
"fullName": "Sheyla Gonzalez Garrido",
"givenName": "Sheyla Gonzalez",
"surname": "Garrido",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of California,Medical Informatics,Los Angeles,CA,USA",
"fullName": "Yu Yan",
"givenName": "Yu",
"surname": "Yan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of California,Medical Informatics,Los Angeles,CA,USA",
"fullName": "Dylan Steinecke",
"givenName": "Dylan",
"surname": "Steinecke",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Stein Eye Institute University of California,Los Angeles,CA,USA",
"fullName": "Elizabeth Rao",
"givenName": "Elizabeth",
"surname": "Rao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Stein Eye Institute University of California,Los Angeles,CA,USA",
"fullName": "Rachel Choi",
"givenName": "Rachel",
"surname": "Choi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Stein Eye Institute University of California,Los Angeles,CA,USA",
"fullName": "Sarah Robertson",
"givenName": "Sarah",
"surname": "Robertson",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Stein Eye Institute University of California,Los Angeles,CA,USA",
"fullName": "Sophie Deng",
"givenName": "Sophie",
"surname": "Deng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of California,Departments of Radiological Sciences,Los Angeles,CA,USA",
"fullName": "Corey Arnold",
"givenName": "Corey",
"surname": "Arnold",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of California,Departments of Radiological Sciences,Los Angeles,CA,USA",
"fullName": "William Speier",
"givenName": "William",
"surname": "Speier",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibe",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-6",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-4261-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09635216",
"articleId": "1zmvvASs1bi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09635556",
"articleId": "1zmvlmrgIcU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibe/2017/1324/0/132401a139",
"title": "3D Segmentation,Visualization and Quantitative Analysis of Differentiation Activity for Mouse Embryonic Stem Cells using Time-Lapse Fluorescence Microscopy Images",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2017/132401a139/12OmNA0vnUP",
"parentPublication": {
"id": "proceedings/bibe/2017/1324/0",
"title": "2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761746",
"title": "Tracking of Arabidopsis thaliana root cells in time-lapse microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761746/12OmNxFsmLs",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2016/07/mco2016070070",
"title": "Enabling Stem Cell Characterization from Large Microscopy Images",
"doi": null,
"abstractUrl": "/magazine/co/2016/07/mco2016070070/13rRUwcAqvA",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2017/04/07962189",
"title": "Mitosis Detection in Phase Contrast Microscopy Image Sequences of Stem Cell Populations: A Critical Review",
"doi": null,
"abstractUrl": "/journal/bd/2017/04/07962189/13rRUxBa5dP",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08546040",
"title": "Multi-label Classification of Stem Cell Microscopy Images Using Deep Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08546040/17D45WZZ7GJ",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669151",
"title": "LncRNA PNKY is upregulated in breast cancer and promotes cell proliferation and EMT in breast cancer cells",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669151/1A9WhZQwxna",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2022/8487/0/848700a174",
"title": "MobileNetV2 Based Diagnosis and Grading of Limbal Stem Cell Deficiency",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2022/848700a174/1J6hGwHNgn6",
"parentPublication": {
"id": "proceedings/bibe/2022/8487/0",
"title": "2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/5555/01/10054500",
"title": "Triplet-net Classification of Contiguous Stem Cell Microscopy Images",
"doi": null,
"abstractUrl": "/journal/tb/5555/01/10054500/1L8lK3OIIJa",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cscc/2020/6503/0/650300a096",
"title": "Structural changes in transcriptional regulatory networks for cell-type-specific gene expression during hematopoiesis",
"doi": null,
"abstractUrl": "/proceedings-article/cscc/2020/650300a096/1t2mVF6spsQ",
"parentPublication": {
"id": "proceedings/cscc/2020/6503/0",
"title": "2020 24th International Conference on Circuits, Systems, Communications and Computers (CSCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100d354",
"title": "DMNet: Dual-Stream Marker Guided Deep Network for Dense Cell Segmentation and Lineage Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100d354/1yNirNbMHqU",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNs4S8wz",
"title": "2014 IEEE International Conference on Information Reuse and Integration (IRI)",
"acronym": "iri",
"groupId": "1001046",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAm4TL2",
"doi": "10.1109/IRI.2014.7051973",
"title": "Bayesian updating for time series missing data discovery and uncertainty estimation (TSMDDUE)",
"normalizedTitle": "Bayesian updating for time series missing data discovery and uncertainty estimation (TSMDDUE)",
"abstract": "In real world applications, it is quite common for datasets to contain missing data due to a variety of limitations. A handful of techniques have been developed to address this problem and impute the missing intervals. The majority of the developed techniques have targeted missing completely at random (MCAR) and missing at random (MAR) datasets and none of them gives a measure of uncertainty. In this paper, the issue of missing data imputation in time series analysis is addressed from a different angle where special attention is devoted to not missing at random (NMAR) datasets and the associated uncertainty characterization. For this purpose, Kriging type techniques as well as Bayesian Updating (BU), commonly used in spatial statistics, are applied and the results are compared to those of more standard techniques. The outcomes of this comparison show the superiority of the adaptedtechniques both in improving predictability and providing the possibility of uncertainty quantification.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In real world applications, it is quite common for datasets to contain missing data due to a variety of limitations. A handful of techniques have been developed to address this problem and impute the missing intervals. The majority of the developed techniques have targeted missing completely at random (MCAR) and missing at random (MAR) datasets and none of them gives a measure of uncertainty. In this paper, the issue of missing data imputation in time series analysis is addressed from a different angle where special attention is devoted to not missing at random (NMAR) datasets and the associated uncertainty characterization. For this purpose, Kriging type techniques as well as Bayesian Updating (BU), commonly used in spatial statistics, are applied and the results are compared to those of more standard techniques. The outcomes of this comparison show the superiority of the adaptedtechniques both in improving predictability and providing the possibility of uncertainty quantification.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In real world applications, it is quite common for datasets to contain missing data due to a variety of limitations. A handful of techniques have been developed to address this problem and impute the missing intervals. The majority of the developed techniques have targeted missing completely at random (MCAR) and missing at random (MAR) datasets and none of them gives a measure of uncertainty. In this paper, the issue of missing data imputation in time series analysis is addressed from a different angle where special attention is devoted to not missing at random (NMAR) datasets and the associated uncertainty characterization. For this purpose, Kriging type techniques as well as Bayesian Updating (BU), commonly used in spatial statistics, are applied and the results are compared to those of more standard techniques. The outcomes of this comparison show the superiority of the adaptedtechniques both in improving predictability and providing the possibility of uncertainty quantification.",
"fno": "07051973",
"keywords": [
"Bayes Methods",
"Uncertainty",
"Time Series Analysis",
"Data Models",
"Correlation Coefficient",
"Autoregressive Processes",
"Correlation"
],
"authors": [
{
"affiliation": "Computer Science Department, University of Calgary, Calgary, AB, Canada",
"fullName": "Sara Aghakhani",
"givenName": "Sara",
"surname": "Aghakhani",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computer Science Department, University of Calgary, Calgary, AB, Canada",
"fullName": "Reda Alhajj",
"givenName": "Reda",
"surname": "Alhajj",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Haskayne School of Business, University of Calgary, Calgary, AB, Canada",
"fullName": "Philip Chang",
"givenName": "Philip",
"surname": "Chang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iri",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-08-01T00:00:00",
"pubType": "proceedings",
"pages": "819-822",
"year": "2014",
"issn": null,
"isbn": "978-1-4799-5880-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "07051972",
"articleId": "12OmNz2kqfM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07051974",
"articleId": "12OmNASraDS",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/grc/2011/0372/0/06122674",
"title": "Hidden dynamic learning for long-interval consecutive missing values reconstruction in EEG time series",
"doi": null,
"abstractUrl": "/proceedings-article/grc/2011/06122674/12OmNAtK4in",
"parentPublication": {
"id": "proceedings/grc/2011/0372/0",
"title": "2011 IEEE International Conference on Granular Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2014/5669/0/06999172",
"title": "Semi-supervised imputation for microarray missing value estimation",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2014/06999172/12OmNqAU6uo",
"parentPublication": {
"id": "proceedings/bibm/2014/5669/0",
"title": "2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccis/2013/5004/0/5004a076",
"title": "Using Seasonal Time Series Analysis to Predict China's Demand of Electricity",
"doi": null,
"abstractUrl": "/proceedings-article/iccis/2013/5004a076/12OmNynJMIW",
"parentPublication": {
"id": "proceedings/iccis/2013/5004/0",
"title": "2013 International Conference on Computational and Information Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2014/4274/0/4274a753",
"title": "Imputation of Missing Values in Time Series with Lagged Correlations",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2014/4274a753/12OmNyp9Mh8",
"parentPublication": {
"id": "proceedings/icdmw/2014/4274/0",
"title": "2014 IEEE International Conference on Data Mining Workshop (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/10032807",
"title": "Selective Imputation for Multivariate Time Series Datasets with Missing Values",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/10032807/1KnSjrR0joQ",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2019/7474/0/747400b976",
"title": "RecovDB: Accurate and Efficient Missing Blocks Recovery for Large Time Series",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2019/747400b976/1aDSTNyeuGc",
"parentPublication": {
"id": "proceedings/icde/2019/7474/0",
"title": "2019 IEEE 35th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09005698",
"title": "NetDyna: Mining Networked Coevolving Time Series with Missing Values",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09005698/1hJrYwk8GfS",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2020/6034/0/603400a303",
"title": "Visual Imputation Analytics for Missing Time-Series Data in Bayesian Network",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2020/603400a303/1jdDwCsHB16",
"parentPublication": {
"id": "proceedings/bigcomp/2020/6034/0",
"title": "2020 IEEE International Conference on Big Data and Smart Computing (BigComp)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09217952",
"title": "A Bayesian cognition approach for belief updating of correlation judgement through uncertainty visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09217952/1nL7qhcUKPe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/09/09380704",
"title": "Bayesian Temporal Factorization for Multidimensional Time Series Prediction",
"doi": null,
"abstractUrl": "/journal/tp/2022/09/09380704/1s2G6IJmuPe",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1jdDt7kZ5jq",
"title": "2020 IEEE International Conference on Big Data and Smart Computing (BigComp)",
"acronym": "bigcomp",
"groupId": "1803439",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1jdDwCsHB16",
"doi": "10.1109/BigComp48618.2020.00-57",
"title": "Visual Imputation Analytics for Missing Time-Series Data in Bayesian Network",
"normalizedTitle": "Visual Imputation Analytics for Missing Time-Series Data in Bayesian Network",
"abstract": "Bayesian network is derived from conditional probability and is useful in inferring the next state of the currently observed variables. If data are missed or corrupted during data collection or transfer, the characteristics of the original data may be distorted and biased. Therefore, predicted values from the Bayesian network designed with incomplete data are not reliable. Various techniques have been studied to resolve the imperfection in data using statistical techniques or machine learning, but since the complete data is unknown, there is no optimal way to impute missing values. In this paper, we present a visual analytics system that supports decision-making to impute missing values occurring in incomplete time series data. The visual analytics system allows data analysts to explore the cause of missing data in incomplete datasets. The system also enables us to compare the performance of a suitable imputation model with the Bayesian network accuracy and the Kolmogorov-Smirnov test. We evaluate how the visual analytics system supports the decision-making process for the data imputation through a use case.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Bayesian network is derived from conditional probability and is useful in inferring the next state of the currently observed variables. If data are missed or corrupted during data collection or transfer, the characteristics of the original data may be distorted and biased. Therefore, predicted values from the Bayesian network designed with incomplete data are not reliable. Various techniques have been studied to resolve the imperfection in data using statistical techniques or machine learning, but since the complete data is unknown, there is no optimal way to impute missing values. In this paper, we present a visual analytics system that supports decision-making to impute missing values occurring in incomplete time series data. The visual analytics system allows data analysts to explore the cause of missing data in incomplete datasets. The system also enables us to compare the performance of a suitable imputation model with the Bayesian network accuracy and the Kolmogorov-Smirnov test. We evaluate how the visual analytics system supports the decision-making process for the data imputation through a use case.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Bayesian network is derived from conditional probability and is useful in inferring the next state of the currently observed variables. If data are missed or corrupted during data collection or transfer, the characteristics of the original data may be distorted and biased. Therefore, predicted values from the Bayesian network designed with incomplete data are not reliable. Various techniques have been studied to resolve the imperfection in data using statistical techniques or machine learning, but since the complete data is unknown, there is no optimal way to impute missing values. In this paper, we present a visual analytics system that supports decision-making to impute missing values occurring in incomplete time series data. The visual analytics system allows data analysts to explore the cause of missing data in incomplete datasets. The system also enables us to compare the performance of a suitable imputation model with the Bayesian network accuracy and the Kolmogorov-Smirnov test. We evaluate how the visual analytics system supports the decision-making process for the data imputation through a use case.",
"fno": "603400a303",
"keywords": [
"Bayes Methods",
"Belief Networks",
"Data Analysis",
"Data Mining",
"Data Visualisation",
"Decision Making",
"Learning Artificial Intelligence",
"Probability",
"Statistical Analysis",
"Time Series",
"Data Collection",
"Incomplete Data",
"Statistical Techniques",
"Complete Data",
"Visual Analytics System",
"Time Series Data",
"Data Analysts",
"Imputation Model",
"Bayesian Network Accuracy",
"Data Imputation",
"Visual Imputation Analytics",
"Time Series Data",
"Conditional Probability",
"Data Visualization",
"Bayes Methods",
"Visual Analytics",
"Data Models",
"Decision Making",
"Analytical Models",
"Visual Analytics Imputation Missing Data Bayesian Network"
],
"authors": [
{
"affiliation": "Sejong University",
"fullName": "Hanbyul Yeon",
"givenName": "Hanbyul",
"surname": "Yeon",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Sejong University",
"fullName": "Hyesook Son",
"givenName": "Hyesook",
"surname": "Son",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Sejong University",
"fullName": "Yun Jang",
"givenName": "Yun",
"surname": "Jang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bigcomp",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-02-01T00:00:00",
"pubType": "proceedings",
"pages": "303-310",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6034-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "603400a295",
"articleId": "1jdDwFOtYek",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "603400a311",
"articleId": "1jdDzI0xd0k",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icci/2009/4642/0/05250727",
"title": "Missing values imputation hypothesis: An experimental evaluation",
"doi": null,
"abstractUrl": "/proceedings-article/icci/2009/05250727/12OmNAOKnXQ",
"parentPublication": {
"id": "proceedings/icci/2009/4642/0",
"title": "Cognitive Informatics, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cit-iucc-dasc-picom/2015/0154/0/07363228",
"title": "A Data Imputation Method Based on Deep Belief Network",
"doi": null,
"abstractUrl": "/proceedings-article/cit-iucc-dasc-picom/2015/07363228/12OmNyrIaKa",
"parentPublication": {
"id": "proceedings/cit-iucc-dasc-picom/2015/0154/0",
"title": "2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2019/03/08303223",
"title": "Microarray Missing Value Imputation: A Regularized Local Learning Method",
"doi": null,
"abstractUrl": "/journal/tb/2019/03/08303223/13rRUy0HYPP",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2018/6051/0/08508716",
"title": "Missing Network Data A Comparison of Different Imputation Methods",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2018/08508716/14Fq0XLgLtM",
"parentPublication": {
"id": "proceedings/asonam/2018/6051/0",
"title": "2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09808164",
"title": "An Experimental Survey of Missing Data Imputation Algorithms",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09808164/1Ey3ZpkY0x2",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995223",
"title": "BayesImpute: a Bayesian imputation method for single-cell RNA-seq data",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995223/1JC34ESwNdS",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020834",
"title": "VIMTS: Variational-based Imputation for Multi-modal Time Series",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020834/1KfRS7ub80U",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2019/9138/0/08904840",
"title": "IEEE ICHI Data Analytics Challenge on Missing data Imputation by Amelia II",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2019/08904840/1f8NbeYRVza",
"parentPublication": {
"id": "proceedings/ichi/2019/9138/0",
"title": "2019 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2021/06/08917717",
"title": "Efficient Utilization of Missing Data in Cost-Sensitive Learning",
"doi": null,
"abstractUrl": "/journal/tk/2021/06/08917717/1gKtGrhpoUE",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09527142",
"title": "Multiple Receding Imputation of Time Series Based on Similar Conditions Screening",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09527142/1wzrJiIt9mM",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNArbG4n",
"title": "2008 5th International Conference on Information Technology: New Generation",
"acronym": "itng",
"groupId": "1001685",
"volume": "0",
"displayVolume": "0",
"year": "2008",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNC2xhCe",
"doi": "10.1109/ITNG.2008.186",
"title": "Plastic Fiber Optic Simulations",
"normalizedTitle": "Plastic Fiber Optic Simulations",
"abstract": "Plastic fiber optics media is viable for small networks. The current applications include data distribution in aircraft and automobiles. Plastic fiber systems being an order of magnitude less expensive than silica fiber optic systems and being more robust have applications in other traditional data communication systems. In this paper, we present the simulation results for possible applications for a high-rise office buildings and premises distribution architectures. The signal to noise ratio for optical rates up to 2.5 Gb/s and for link lengths up to 5 km are reported, even though the signal level becomes too low for the PIN diodes. The quality of components affects the performance dramatically and their impact is reported. Experimental results are scarce in the literature for either of the two (PMMA and PF) categories of commercial plastic fibers. The simulations are focused for the PMMA plastic fiber to offer a window and envision other applications for this new breed of optical fibers.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Plastic fiber optics media is viable for small networks. The current applications include data distribution in aircraft and automobiles. Plastic fiber systems being an order of magnitude less expensive than silica fiber optic systems and being more robust have applications in other traditional data communication systems. In this paper, we present the simulation results for possible applications for a high-rise office buildings and premises distribution architectures. The signal to noise ratio for optical rates up to 2.5 Gb/s and for link lengths up to 5 km are reported, even though the signal level becomes too low for the PIN diodes. The quality of components affects the performance dramatically and their impact is reported. Experimental results are scarce in the literature for either of the two (PMMA and PF) categories of commercial plastic fibers. The simulations are focused for the PMMA plastic fiber to offer a window and envision other applications for this new breed of optical fibers.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Plastic fiber optics media is viable for small networks. The current applications include data distribution in aircraft and automobiles. Plastic fiber systems being an order of magnitude less expensive than silica fiber optic systems and being more robust have applications in other traditional data communication systems. In this paper, we present the simulation results for possible applications for a high-rise office buildings and premises distribution architectures. The signal to noise ratio for optical rates up to 2.5 Gb/s and for link lengths up to 5 km are reported, even though the signal level becomes too low for the PIN diodes. The quality of components affects the performance dramatically and their impact is reported. Experimental results are scarce in the literature for either of the two (PMMA and PF) categories of commercial plastic fibers. The simulations are focused for the PMMA plastic fiber to offer a window and envision other applications for this new breed of optical fibers.",
"fno": "3099b228",
"keywords": [
"Plastic Fiber Optics",
"Simulations",
"Data Rates",
"Ranges",
"Applications"
],
"authors": [
{
"affiliation": null,
"fullName": "Syed V. Ahamed",
"givenName": "Syed V.",
"surname": "Ahamed",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Galathara Ananda Kahanda",
"givenName": "Galathara Ananda",
"surname": "Kahanda",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "itng",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2008-04-01T00:00:00",
"pubType": "proceedings",
"pages": "1228-1233",
"year": "2008",
"issn": null,
"isbn": "978-0-7695-3099-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3099b226",
"articleId": "12OmNvIfDQj",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3099b234",
"articleId": "12OmNzn38ZR",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icacte/2008/3489/0/3489b040",
"title": "A Reservation Protocols Based on Slotted ALOHA for Plastic Optical Fiber Network",
"doi": null,
"abstractUrl": "/proceedings-article/icacte/2008/3489b040/12OmNAWH9ud",
"parentPublication": {
"id": "proceedings/icacte/2008/3489/0",
"title": "2008 International Conference on Advanced Computer Theory and Engineering (ICACTE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscsct/2008/3498/2/3498b471",
"title": "Analysis and Simulation Protocols Based on Slotted ALOHA for Plastic Optical Fiber Network",
"doi": null,
"abstractUrl": "/proceedings-article/iscsct/2008/3498b471/12OmNC2xhzb",
"parentPublication": {
"id": "proceedings/iscsct/2008/3498/1",
"title": "2008 International Symposium on Computer Science and Computational Technology (ISCSCT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dcabes/2017/2162/0/2162a127",
"title": "Core Technology for Achieving Plastic Optical Fibers in an All-Optical Network",
"doi": null,
"abstractUrl": "/proceedings-article/dcabes/2017/2162a127/12OmNqC2v0D",
"parentPublication": {
"id": "proceedings/dcabes/2017/2162/0",
"title": "2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2010/4077/2/4077c254",
"title": "Experimental Investigation of Coupling Fiber-Optic Vibration Sensor",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2010/4077c254/12OmNrJRPoO",
"parentPublication": {
"id": "proceedings/icicta/2010/4077/2",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icece/2010/4031/0/4031a936",
"title": "Experimental Investigation of Coupling Fiber-Optic Sensor for Vibration Measurement",
"doi": null,
"abstractUrl": "/proceedings-article/icece/2010/4031a936/12OmNwMFMgP",
"parentPublication": {
"id": "proceedings/icece/2010/4031/0",
"title": "Electrical and Control Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/1994/2413/0/00580484",
"title": "Fiber optic experiments for electrical/optical engineering technology laboratories",
"doi": null,
"abstractUrl": "/proceedings-article/fie/1994/00580484/12OmNwdbV6Y",
"parentPublication": {
"id": "proceedings/fie/1994/2413/0",
"title": "Proceedings of 1994 IEEE Frontiers in Education Conference - FIE '94",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fgcn/2014/7779/0/07024354",
"title": "Simulation of Polarization Errors for All-Fiber Optic Current Sensors",
"doi": null,
"abstractUrl": "/proceedings-article/fgcn/2014/07024354/12OmNzYNN5u",
"parentPublication": {
"id": "proceedings/fgcn/2014/7779/0",
"title": "2014 8th International Conference on Future Generation Communication and Networking (FGCN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mi/1996/01/m1020",
"title": "Parallel Fiber-Optic SCI Links",
"doi": null,
"abstractUrl": "/magazine/mi/1996/01/m1020/13rRUwhHcNd",
"parentPublication": {
"id": "mags/mi",
"title": "IEEE Micro",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iseeie/2022/6874/0/687400a247",
"title": "Weight Measurement System Using Plastic Optical Fiber",
"doi": null,
"abstractUrl": "/proceedings-article/iseeie/2022/687400a247/1FWmK93ufWo",
"parentPublication": {
"id": "proceedings/iseeie/2022/6874/0",
"title": "2022 International Symposium on Electrical, Electronics and Information Engineering (ISEEIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icapc/2022/6303/0/630300a337",
"title": "Probe design of reflective fiber optic hydrogen sensor",
"doi": null,
"abstractUrl": "/proceedings-article/icapc/2022/630300a337/1M7KXPskuxa",
"parentPublication": {
"id": "proceedings/icapc/2022/6303/0",
"title": "2022 International Conference on Applied Physics and Computing (ICAPC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNs0kyrq",
"title": "2006 Winter Simulation Conference",
"acronym": "wsc",
"groupId": "1000674",
"volume": "0",
"displayVolume": "0",
"year": "2006",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNC3o50F",
"doi": "10.1109/WSC.2006.323035",
"title": "Introduction to Modeling and Generating Probabilistic Input Processes for Simulation",
"normalizedTitle": "Introduction to Modeling and Generating Probabilistic Input Processes for Simulation",
"abstract": "Techniques are presented for modeling and generating the univariate and multivariate probabilistic input processes that drive many simulation experiments. Among univariate input models, emphasis is given to the generalized beta distribution family, the Johnson translation system of distributions, and the Bezier distribution family. Among bivariate and higher-dimensional input models, emphasis is given to computationally tractable extensions of univariate Johnson distributions. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogeneous Poisson processes",
"abstracts": [
{
"abstractType": "Regular",
"content": "Techniques are presented for modeling and generating the univariate and multivariate probabilistic input processes that drive many simulation experiments. Among univariate input models, emphasis is given to the generalized beta distribution family, the Johnson translation system of distributions, and the Bezier distribution family. Among bivariate and higher-dimensional input models, emphasis is given to computationally tractable extensions of univariate Johnson distributions. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogeneous Poisson processes",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Techniques are presented for modeling and generating the univariate and multivariate probabilistic input processes that drive many simulation experiments. Among univariate input models, emphasis is given to the generalized beta distribution family, the Johnson translation system of distributions, and the Bezier distribution family. Among bivariate and higher-dimensional input models, emphasis is given to computationally tractable extensions of univariate Johnson distributions. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogeneous Poisson processes",
"fno": "04117588",
"keywords": [
"Probabilistic Input Processes",
"Multivariate Probabilistic",
"Univariate Probabilistic",
"Generalized Beta Distribution",
"Johnson Translation System",
"Bezier Distribution Family",
"Higher Dimensional Input Models",
"Univariate Johnson Distributions",
"Nonhomogeneous Poisson Processes"
],
"authors": [
{
"affiliation": "Dept. of Ind.&Syst. Eng., Rochester Inst. of Technol., NY",
"fullName": "M.E. Kuhl",
"givenName": "M.E.",
"surname": "Kuhl",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "E.K. Eada",
"givenName": "E.K.",
"surname": "Eada",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "N.M. Steiger",
"givenName": "N.M.",
"surname": "Steiger",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "M.A. Wagner",
"givenName": "M.A.",
"surname": "Wagner",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "J.R. Wilson",
"givenName": "J.R.",
"surname": "Wilson",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wsc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2006-12-01T00:00:00",
"pubType": "proceedings",
"pages": "19-35",
"year": "2006",
"issn": null,
"isbn": "1-4244-0500-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "04117587",
"articleId": "12OmNxG1yJV",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "04117589",
"articleId": "12OmNA14Aaa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wsc/1988/42/0/00716141",
"title": "Input modeling with the Johnson System of distributions",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/1988/00716141/12OmNqGA4ZU",
"parentPublication": {
"id": "proceedings/wsc/1988/42/0",
"title": "1988 Winter Simulation Conference Proceedings",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/1989/58/0/00718694",
"title": "Modeling Input Processes With Johnson Distributions",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/1989/00718694/12OmNrIJqyr",
"parentPublication": {
"id": "proceedings/wsc/1989/58/0",
"title": "Winter Simulation Conference Proceedings 1989",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/micai/2009/3933/0/3933a003",
"title": "Comparison of Two Evolvable Systems in the Automated Analog Circuit Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/micai/2009/3933a003/12OmNrJAdPJ",
"parentPublication": {
"id": "proceedings/micai/2009/3933/0",
"title": "2009 Eighth Mexican International Conference on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/synasc/2014/8447/0/07034683",
"title": "Simulation-Extrapolation Gaussian Processes for Input Noise Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/synasc/2014/07034683/12OmNvs4vot",
"parentPublication": {
"id": "proceedings/synasc/2014/8447/0",
"title": "2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/1993/1381/0/00718073",
"title": "Using Univariate Bezier Distributions to Model Simulation Input Processes",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/1993/00718073/12OmNxI0Kwe",
"parentPublication": {
"id": "proceedings/wsc/1993/1381/0",
"title": "Proceedings of 1993 Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/2002/7614/1/01172893",
"title": "Parameter estimation for ARTA processes",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/2002/01172893/12OmNzVXNVY",
"parentPublication": {
"id": "proceedings/wsc/2002/7614/1",
"title": "Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/1996/3383/0/00873462",
"title": "Multivariate input modeling with johnson distributions",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/1996/00873462/1D89l2hqjoA",
"parentPublication": {
"id": "proceedings/wsc/1996/3383/0",
"title": "Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/1996/3383/0/00873461",
"title": "Recent developments in input modeling with bezier distributions",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/1996/00873461/1D89uE8ik7e",
"parentPublication": {
"id": "proceedings/wsc/1996/3383/0",
"title": "Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300f300",
"title": "Probabilistic Deep Ordinal Regression Based on Gaussian Processes",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300f300/1hVlQDFcat2",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800a062",
"title": "Generating and Exploiting Probabilistic Monocular Depth Estimates",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800a062/1m3o34Lbc40",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAY79o7",
"title": "Computer Communications and Networks, International Conference on",
"acronym": "icccn",
"groupId": "1000127",
"volume": "0",
"displayVolume": "0",
"year": "1998",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNx8OuxI",
"doi": "10.1109/ICCCN.1998.739952",
"title": "Wavelength Assignment for Dynamic Traffic in Multi-fiber WDM Networks",
"normalizedTitle": "Wavelength Assignment for Dynamic Traffic in Multi-fiber WDM Networks",
"abstract": "We propose an on-line wavelength assignment algorithm for multi-fiber WDM networks, in which lightpaths are established and released dynamically. For a given number of fibers per link and number of wavelengths per fiber, the algorithm aims to minimize the blocking probability. It may also be used to reduce the number of wavelengths required for a given tolerable blocking probability. Simulation results show that our wavelength assignment algorithm performs better than other previously proposed algorithms (in the cases we studied). As the number of fibers per link increases, the benefit of having wavelength converters decreases dramatically, and the performance improvement of our algorithm over others increases. Our results also show that in case a preferred path is not available, rerouting along a node-disjoint backup path can significantly reduce the blocking probability.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose an on-line wavelength assignment algorithm for multi-fiber WDM networks, in which lightpaths are established and released dynamically. For a given number of fibers per link and number of wavelengths per fiber, the algorithm aims to minimize the blocking probability. It may also be used to reduce the number of wavelengths required for a given tolerable blocking probability. Simulation results show that our wavelength assignment algorithm performs better than other previously proposed algorithms (in the cases we studied). As the number of fibers per link increases, the benefit of having wavelength converters decreases dramatically, and the performance improvement of our algorithm over others increases. Our results also show that in case a preferred path is not available, rerouting along a node-disjoint backup path can significantly reduce the blocking probability.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose an on-line wavelength assignment algorithm for multi-fiber WDM networks, in which lightpaths are established and released dynamically. For a given number of fibers per link and number of wavelengths per fiber, the algorithm aims to minimize the blocking probability. It may also be used to reduce the number of wavelengths required for a given tolerable blocking probability. Simulation results show that our wavelength assignment algorithm performs better than other previously proposed algorithms (in the cases we studied). As the number of fibers per link increases, the benefit of having wavelength converters decreases dramatically, and the performance improvement of our algorithm over others increases. Our results also show that in case a preferred path is not available, rerouting along a node-disjoint backup path can significantly reduce the blocking probability.",
"fno": "90140479",
"keywords": [
"WDM",
"Wavelength Assignment",
"Multi Fiber Networks",
"Blocking Probability"
],
"authors": [
{
"affiliation": "SUNY/Buffalo",
"fullName": "Xijun Zhang",
"givenName": "Xijun",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "SUNY/Buffalo",
"fullName": "Chunming Qiao",
"givenName": "Chunming",
"surname": "Qiao",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icccn",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1998-10-01T00:00:00",
"pubType": "proceedings",
"pages": "479",
"year": "1998",
"issn": "1095-2055",
"isbn": "0-8186-9014-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "90140472",
"articleId": "12OmNy5zsqL",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "90140486",
"articleId": "12OmNCbkQBr",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNrAMEOf",
"title": "2017 13th International Conference on Computational Intelligence and Security (CIS)",
"acronym": "cis",
"groupId": "1001517",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNy1SFFZ",
"doi": "10.1109/CIS.2017.00049",
"title": "Bayesian Spatial Nonparametric Models for Confounding Manifest Variables with an Application to China Earthquake Data",
"normalizedTitle": "Bayesian Spatial Nonparametric Models for Confounding Manifest Variables with an Application to China Earthquake Data",
"abstract": "We consider a Bayesian nonparametric models for spatial data of mixed category. Moreover, we adopt joint modeling strategy by assuming that responses and confounding variables are corresponding to continuous latent variables with multivariate Gaussian distribution. The model is built on a class of Gaussian Conditional Autoregressive (CAR) models, in combination with dependent sampling models (SSM) as well as probit stick-breaking process prior for accounting for complex interactions and high correlations of data. The key idea is to introducing spatial dependence by modeling the weights via probit transformation of Gaussian Markov random fields or discrete random probability measures of SSM. We illustrate the usefulness and effectiveness of the methodology through a real example from a China earthquake data set.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We consider a Bayesian nonparametric models for spatial data of mixed category. Moreover, we adopt joint modeling strategy by assuming that responses and confounding variables are corresponding to continuous latent variables with multivariate Gaussian distribution. The model is built on a class of Gaussian Conditional Autoregressive (CAR) models, in combination with dependent sampling models (SSM) as well as probit stick-breaking process prior for accounting for complex interactions and high correlations of data. The key idea is to introducing spatial dependence by modeling the weights via probit transformation of Gaussian Markov random fields or discrete random probability measures of SSM. We illustrate the usefulness and effectiveness of the methodology through a real example from a China earthquake data set.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We consider a Bayesian nonparametric models for spatial data of mixed category. Moreover, we adopt joint modeling strategy by assuming that responses and confounding variables are corresponding to continuous latent variables with multivariate Gaussian distribution. The model is built on a class of Gaussian Conditional Autoregressive (CAR) models, in combination with dependent sampling models (SSM) as well as probit stick-breaking process prior for accounting for complex interactions and high correlations of data. The key idea is to introducing spatial dependence by modeling the weights via probit transformation of Gaussian Markov random fields or discrete random probability measures of SSM. We illustrate the usefulness and effectiveness of the methodology through a real example from a China earthquake data set.",
"fno": "482201a192",
"keywords": [
"Autoregressive Processes",
"Bayes Methods",
"Data Handling",
"Earthquakes",
"Gaussian Distribution",
"Gaussian Processes",
"Markov Processes",
"Nonparametric Statistics",
"Sampling Methods",
"Bayesian Spatial Nonparametric Models",
"Manifest Variables",
"China Earthquake Data",
"Bayesian Nonparametric Models",
"Spatial Data",
"Mixed Category",
"Joint Modeling Strategy",
"Confounding Variables",
"Continuous Latent Variables",
"Multivariate Gaussian Distribution",
"Gaussian Conditional Autoregressive Models",
"Dependent Sampling Models",
"SSM",
"Probit Stick Breaking Process",
"Spatial Dependence",
"Gaussian Markov Random Fields",
"Biological System Modeling",
"Automobiles",
"Data Models",
"Earthquakes",
"Analytical Models",
"Bayes Methods",
"Gaussian Distribution",
"Bayesian Analysis",
"Spatial Heterogeneity",
"Probit Sitck Breaking Process Prior",
"Gaussian Conditional Autoregression Mode"
],
"authors": [
{
"affiliation": null,
"fullName": "Yingzi Fu",
"givenName": "Yingzi",
"surname": "Fu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Dexin Ren",
"givenName": "Dexin",
"surname": "Ren",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-12-01T00:00:00",
"pubType": "proceedings",
"pages": "192-196",
"year": "2017",
"issn": null,
"isbn": "978-1-5386-4822-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "482201a187",
"articleId": "12OmNwvVrHB",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "482201a197",
"articleId": "12OmNA1DMnF",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdm/2015/9504/0/9504a967",
"title": "Nonparametric Poisson Factorization Machine",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2015/9504a967/12OmNwOnn1M",
"parentPublication": {
"id": "proceedings/icdm/2015/9504/0",
"title": "2015 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2003/1900/1/190010605",
"title": "Nonparametric Belief Propagation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2003/190010605/12OmNyQYtxY",
"parentPublication": {
"id": "proceedings/cvpr/2003/1900/1",
"title": "2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/snpd/2013/5005/0/5005a219",
"title": "A Multiway Model for Predicting Earthquake Ground Motion",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2013/5005a219/12OmNz61dix",
"parentPublication": {
"id": "proceedings/snpd/2013/5005/0",
"title": "2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2014/11/06786502",
"title": "Pseudo-Marginal Bayesian Inference for Gaussian Processes",
"doi": null,
"abstractUrl": "/journal/tp/2014/11/06786502/13rRUwbJD66",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2008/02/04403040",
"title": "Exact distribution of the max/min of two Gaussian random variables",
"doi": null,
"abstractUrl": "/journal/si/2008/02/04403040/13rRUx0gesP",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2015/02/06654132",
"title": "Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model",
"doi": null,
"abstractUrl": "/journal/tp/2015/02/06654132/13rRUxZ0o2M",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2015/02/06629993",
"title": "Bayesian Nonparametric Models for Multiway Data Analysis",
"doi": null,
"abstractUrl": "/journal/tp/2015/02/06629993/13rRUxly8Uh",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10020430",
"title": "Bayesian Nonparametric Model Averaging Using Scalable Gaussian Process Representations",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10020430/1KfSewnKaOY",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2021/06/08902053",
"title": "Nonparametric Regression via Variance-Adjusted Gradient Boosting Gaussian Process Regression",
"doi": null,
"abstractUrl": "/journal/tk/2021/06/08902053/1eYN6682xnW",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaa/2021/3730/0/373000a986",
"title": "Application of the Random Forest Kernel in Nonparametric Regression Model with Spherical Variables",
"doi": null,
"abstractUrl": "/proceedings-article/icaa/2021/373000a986/1zL1M0EXeeY",
"parentPublication": {
"id": "proceedings/icaa/2021/3730/0",
"title": "2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNz61dBt",
"title": "2010 14th International Conference Information Visualisation",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNCxbXKy",
"doi": "10.1109/IV.2010.99",
"title": "From Data Realism to Dada Aggregations: Visualizations in Digital Art, Humanities and Popular Culture",
"normalizedTitle": "From Data Realism to Dada Aggregations: Visualizations in Digital Art, Humanities and Popular Culture",
"abstract": "The orientation towards data in arts, humanities and pop culture in recent years brings a renewed interest in realism and iconoclasm. The various APIs (Application programming interfaces) and mashups that are employed in these traditionally “qualitative” disciplines offer tools for creative and often critical interpretations. Data are becoming means of a critical distance to the visual and media saturated world that bring whole new perspective on our everyday life and reality. These emerging critical and visual practices define a realism based on data rather than on human perception, reason or some strong ontological theses. This data oriented realism does not simply represent reality but performs the modern processes of its construction with an almost iconoclastic fervor. It offers a distance from the power and seduction of the (digital) image and asks questions about their conditions of possibility, methods of gathering and the various possibilities of their representation. Visualization of various data in the form of popular user generated mashups, serious art visualizations and new digital methods in humanities create a tension between the new forms of iconoclastic realism and the more playful dada collage techniques that are satirical and rather than realist and emancipatory rather than iconoclastic. The use of visualizations in art, humanities and online popular culture (cyberculture) is defined by this tension between data realism to dada “aggregations”.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The orientation towards data in arts, humanities and pop culture in recent years brings a renewed interest in realism and iconoclasm. The various APIs (Application programming interfaces) and mashups that are employed in these traditionally “qualitative” disciplines offer tools for creative and often critical interpretations. Data are becoming means of a critical distance to the visual and media saturated world that bring whole new perspective on our everyday life and reality. These emerging critical and visual practices define a realism based on data rather than on human perception, reason or some strong ontological theses. This data oriented realism does not simply represent reality but performs the modern processes of its construction with an almost iconoclastic fervor. It offers a distance from the power and seduction of the (digital) image and asks questions about their conditions of possibility, methods of gathering and the various possibilities of their representation. Visualization of various data in the form of popular user generated mashups, serious art visualizations and new digital methods in humanities create a tension between the new forms of iconoclastic realism and the more playful dada collage techniques that are satirical and rather than realist and emancipatory rather than iconoclastic. The use of visualizations in art, humanities and online popular culture (cyberculture) is defined by this tension between data realism to dada “aggregations”.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The orientation towards data in arts, humanities and pop culture in recent years brings a renewed interest in realism and iconoclasm. The various APIs (Application programming interfaces) and mashups that are employed in these traditionally “qualitative” disciplines offer tools for creative and often critical interpretations. Data are becoming means of a critical distance to the visual and media saturated world that bring whole new perspective on our everyday life and reality. These emerging critical and visual practices define a realism based on data rather than on human perception, reason or some strong ontological theses. This data oriented realism does not simply represent reality but performs the modern processes of its construction with an almost iconoclastic fervor. It offers a distance from the power and seduction of the (digital) image and asks questions about their conditions of possibility, methods of gathering and the various possibilities of their representation. Visualization of various data in the form of popular user generated mashups, serious art visualizations and new digital methods in humanities create a tension between the new forms of iconoclastic realism and the more playful dada collage techniques that are satirical and rather than realist and emancipatory rather than iconoclastic. The use of visualizations in art, humanities and online popular culture (cyberculture) is defined by this tension between data realism to dada “aggregations”.",
"fno": "05571256",
"keywords": [
"Application Program Interfaces",
"Art",
"Data Visualisation",
"Ontologies Artificial Intelligence",
"Data Realism",
"Dada Aggregations",
"Digital Art",
"Iconoclasm",
"Application Programming Interfaces",
"Mashups",
"Ontological Theses",
"Art Visualizations",
"Dada Collage Techniques",
"Data Visualization",
"Mashups",
"Humans",
"Visualization",
"Cultural Differences",
"Digital Art",
"Realis",
"Data",
"Art",
"API",
"Mashup",
"Critical Distance",
"Visualization",
"Dada",
"Collage"
],
"authors": [
{
"affiliation": null,
"fullName": "Denisa Kera",
"givenName": "Denisa",
"surname": "Kera",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-07-01T00:00:00",
"pubType": "proceedings",
"pages": "297-300",
"year": "2010",
"issn": "1550-6037",
"isbn": "978-1-4244-7846-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05571255",
"articleId": "12OmNwCsdBt",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05571249",
"articleId": "12OmNzX6cmV",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/jcdl/2016/4229/0/07559604",
"title": "Visualizing published metadata in large aggregations",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2016/07559604/12OmNAGNCfS",
"parentPublication": {
"id": "proceedings/jcdl/2016/4229/0",
"title": "2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2006/2734/0/04031108",
"title": "Educating the Humanities for e-Science",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2006/04031108/12OmNqN6R7C",
"parentPublication": {
"id": "proceedings/e-science/2006/2734/0",
"title": "2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isdea/2013/2792/0/06843522",
"title": "Study on University Buildings Ecology Based on Humanities Ecological Environment",
"doi": null,
"abstractUrl": "/proceedings-article/isdea/2013/06843522/12OmNwHQB27",
"parentPublication": {
"id": "proceedings/isdea/2013/2792/0",
"title": "2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications (ISDEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2009/5946/0/05407965",
"title": "Geospatial computing for the arts, humanities and cultural heritage",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2009/05407965/12OmNwfsI4N",
"parentPublication": {
"id": "proceedings/e-science/2009/5946/0",
"title": "2009 5th IEEE International Conference on e-Science Workshops (e-science 2009)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2013/0965/0/06624242",
"title": "Smoke and Shadows: Rendering and Light Interaction of Smoke in Real-Time Rendered Virtual Environments",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2013/06624242/12OmNxXCGIU",
"parentPublication": {
"id": "proceedings/vs-games/2013/0965/0",
"title": "2013 5th International Conference on Games and Virtual Worlds for Serious Applications (VS-GAMES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/culture-computing/2013/5047/0/5047a196",
"title": "Improving User Control and Transparency in the Digital Humanities",
"doi": null,
"abstractUrl": "/proceedings-article/culture-computing/2013/5047a196/12OmNylKAPW",
"parentPublication": {
"id": "proceedings/culture-computing/2013/5047/0",
"title": "2013 International Conference on Culture and Computing (Culture Computing)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192666",
"title": "Speculative Practices: Utilizing InfoVis to Explore Untapped Literary Collections",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192666/13rRUB7a113",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2020/03/09057396",
"title": "Many Views Are Not Enough: Designing for Synoptic Insights in Cultural Collections",
"doi": null,
"abstractUrl": "/magazine/cg/2020/03/09057396/1iUHRAGtNOE",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/beliv/2020/9642/0/964200a029",
"title": "Using Close Reading as a Method for Evaluating Visualizations",
"doi": null,
"abstractUrl": "/proceedings-article/beliv/2020/964200a029/1q0FO3J5Ogg",
"parentPublication": {
"id": "proceedings/beliv/2020/9642/0",
"title": "2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2021/1770/0/177000a246",
"title": "Exploring the Classification of Traditional Chinese Bibliographies through Interactive Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2021/177000a246/1zJmYfHdJ7O",
"parentPublication": {
"id": "proceedings/jcdl/2021/1770/0",
"title": "2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNvkYx8t",
"title": "2011 44th Hawaii International Conference on System Sciences",
"acronym": "hicss",
"groupId": "1000730",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNs5rl2f",
"doi": "10.1109/HICSS.2011.353",
"title": "Purposeful Visualization",
"normalizedTitle": "Purposeful Visualization",
"abstract": "In spite of rapid and many advances in the field of visualizations there are still fundamental problems that beset it. We propose the concept of purposeful visualization (PV) as a means of addressing the key problems by highlighting the importance of purpose and context when we consider, design, use, and evaluate visualizations. PVs fulfill a particular purpose for one or more stakeholders within a certain context. The key objectives of our research were to explore and understand purposeful and beautiful visualizations, formalize a definition of such purposeful visualizations that will enable us to explore this concept further, design and implement a system to explore, analyze and evaluate PVs and finally propose a taxonomy and a model of PVs to support the design and evaluation of PVs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In spite of rapid and many advances in the field of visualizations there are still fundamental problems that beset it. We propose the concept of purposeful visualization (PV) as a means of addressing the key problems by highlighting the importance of purpose and context when we consider, design, use, and evaluate visualizations. PVs fulfill a particular purpose for one or more stakeholders within a certain context. The key objectives of our research were to explore and understand purposeful and beautiful visualizations, formalize a definition of such purposeful visualizations that will enable us to explore this concept further, design and implement a system to explore, analyze and evaluate PVs and finally propose a taxonomy and a model of PVs to support the design and evaluation of PVs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In spite of rapid and many advances in the field of visualizations there are still fundamental problems that beset it. We propose the concept of purposeful visualization (PV) as a means of addressing the key problems by highlighting the importance of purpose and context when we consider, design, use, and evaluate visualizations. PVs fulfill a particular purpose for one or more stakeholders within a certain context. The key objectives of our research were to explore and understand purposeful and beautiful visualizations, formalize a definition of such purposeful visualizations that will enable us to explore this concept further, design and implement a system to explore, analyze and evaluate PVs and finally propose a taxonomy and a model of PVs to support the design and evaluation of PVs.",
"fno": "05718471",
"keywords": [
"Data Visualisation",
"Information Systems",
"Purposeful Visualization",
"Information Visualization",
"Data Visualization",
"Seminars",
"Visualization",
"Context",
"Prototypes",
"Taxonomy",
"Data Analysis"
],
"authors": [
{
"affiliation": null,
"fullName": "Xiaoyan Bai",
"givenName": "Xiaoyan",
"surname": "Bai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "David White",
"givenName": "David",
"surname": "White",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "David Sundaram",
"givenName": "David",
"surname": "Sundaram",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "hicss",
"isOpenAccess": true,
"showRecommendedArticles": true,
"showBuyMe": false,
"hasPdf": true,
"pubDate": "2011-01-01T00:00:00",
"pubType": "proceedings",
"pages": "1-10",
"year": "2011",
"issn": "1530-1605",
"isbn": "978-1-4244-9618-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05718470",
"articleId": "12OmNzVoBSZ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05718472",
"articleId": "12OmNrkT7Od",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2015/7568/0/7568a140",
"title": "Towards the Understanding of Interaction in Information Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2015/7568a140/12OmNBQ2VVu",
"parentPublication": {
"id": "proceedings/iv/2015/7568/0",
"title": "2015 19th International Conference on Information Visualisation (iV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wcse/2010/4303/1/4303a241",
"title": "Purposeful Visualization System",
"doi": null,
"abstractUrl": "/proceedings-article/wcse/2010/4303a241/12OmNvUaNgj",
"parentPublication": {
"id": "wcse/2010/4303/1",
"title": "2010 Second World Congress on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2016/8942/0/8942a203",
"title": "Promoting Insight: A Case Study of How to Incorporate Interaction in Existing Data Visualizations",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2016/8942a203/12OmNx7G68T",
"parentPublication": {
"id": "proceedings/iv/2016/8942/0",
"title": "2016 20th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scivis/2015/9785/0/07429511",
"title": "A proposed multivariate visualization taxonomy from user data",
"doi": null,
"abstractUrl": "/proceedings-article/scivis/2015/07429511/12OmNzmLxKh",
"parentPublication": {
"id": "proceedings/scivis/2015/9785/0",
"title": "2015 IEEE Scientific Visualization Conference (SciVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013122306",
"title": "What Makes a Visualization Memorable?",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122306/13rRUxE04tz",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/01/08017594",
"title": "The Explanatory Visualization Framework: An Active Learning Framework for Teaching Creative Computing Using Explanatory Visualizations",
"doi": null,
"abstractUrl": "/journal/tg/2018/01/08017594/13rRUyY28YC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903547",
"title": "Cultivating Visualization Literacy for Children Through Curiosity and Play",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903547/1GZookEFGzC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904442",
"title": "Communicating Uncertainty in Digital Humanities Visualization Research",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904442/1H1gpt871W8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/12/09528956",
"title": "Multiscale Visualization: A Structured Literature Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2022/12/09528956/1wB2xUo1WKY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2021/06/09556564",
"title": "A Taxonomy-Driven Model for Designing Educational Games in Visualization",
"doi": null,
"abstractUrl": "/magazine/cg/2021/06/09556564/1xlw4DK3GXC",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J2XGOP3M1G",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"acronym": "vis4dh",
"groupId": "1839705",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J2XHbXW4xO",
"doi": "10.1109/VIS4DH57440.2022.00006",
"title": "Boundaries, Extensions, and Challenges of Visualization for Humanities Data: Reflections on Three Cases",
"normalizedTitle": "Boundaries, Extensions, and Challenges of Visualization for Humanities Data: Reflections on Three Cases",
"abstract": "This paper discusses problems of visualizing humanities data of various forms, such as video data, archival data, and numeric-oriented social science data, with three distinct case studies. By describing the visualization practices and the issues that emerged from the process, this paper uses the three cases to each identify a pertinent question for reflection. More specifically, I reflect on the difficulty, thoughts, and considerations of choosing the most effective and sufficient forms of visualization to enhance the expression of specific cultural and humanities data in the projects. Discussions in this paper concern some questions, such as, how do the multi-modality of humanities and cultural data challenge the understanding, roles, and functions of visualizations, and more broadly, visual representations in humanities research? What do we lose of the original data by visualizing them in those projects? How to balance the benefits and disadvantages of visual technologies to display complex, unique, and often culturally saturated humanities datasets?",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper discusses problems of visualizing humanities data of various forms, such as video data, archival data, and numeric-oriented social science data, with three distinct case studies. By describing the visualization practices and the issues that emerged from the process, this paper uses the three cases to each identify a pertinent question for reflection. More specifically, I reflect on the difficulty, thoughts, and considerations of choosing the most effective and sufficient forms of visualization to enhance the expression of specific cultural and humanities data in the projects. Discussions in this paper concern some questions, such as, how do the multi-modality of humanities and cultural data challenge the understanding, roles, and functions of visualizations, and more broadly, visual representations in humanities research? What do we lose of the original data by visualizing them in those projects? How to balance the benefits and disadvantages of visual technologies to display complex, unique, and often culturally saturated humanities datasets?",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper discusses problems of visualizing humanities data of various forms, such as video data, archival data, and numeric-oriented social science data, with three distinct case studies. By describing the visualization practices and the issues that emerged from the process, this paper uses the three cases to each identify a pertinent question for reflection. More specifically, I reflect on the difficulty, thoughts, and considerations of choosing the most effective and sufficient forms of visualization to enhance the expression of specific cultural and humanities data in the projects. Discussions in this paper concern some questions, such as, how do the multi-modality of humanities and cultural data challenge the understanding, roles, and functions of visualizations, and more broadly, visual representations in humanities research? What do we lose of the original data by visualizing them in those projects? How to balance the benefits and disadvantages of visual technologies to display complex, unique, and often culturally saturated humanities datasets?",
"fno": "766800a001",
"keywords": [
"Data Visualisation",
"Humanities",
"Archival Data",
"Cultural Data",
"Humanities Data Visualization",
"Humanities Datasets",
"Numeric Oriented Social Science Data",
"Video Data",
"Visual Representations",
"Visual Technologies",
"Human Computer Interaction",
"Humanities",
"Visualization",
"Conferences",
"Social Sciences",
"Data Visualization",
"Reflection",
"Human Centered Computing Visualization",
"Visualization Application Domains",
"Information Visualization"
],
"authors": [
{
"affiliation": "Indiana University Bloomington",
"fullName": "Rongqian Ma",
"givenName": "Rongqian",
"surname": "Ma",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vis4dh",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-5",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-7668-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "766800z007",
"articleId": "1J2XHUn1x7y",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "766800a006",
"articleId": "1J2XIfWP19C",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/e-science/2009/5946/0/05407965",
"title": "Geospatial computing for the arts, humanities and cultural heritage",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2009/05407965/12OmNwfsI4N",
"parentPublication": {
"id": "proceedings/e-science/2009/5946/0",
"title": "2009 5th IEEE International Conference on e-Science Workshops (e-science 2009)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2009/5340/0/3877a028",
"title": "Integrating Full-Text Search and Linguistic Analyses on Disperse Data for Humanities and Social Sciences Research Projects",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2009/3877a028/12OmNxVDuNe",
"parentPublication": {
"id": "proceedings/e-science/2009/5340/0",
"title": "2009 5th IEEE International Conference on e-Science (e-Science 2009)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2011/4520/0/4520b017",
"title": "The Four and a Half Challenges of Humanities Data",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2011/4520b017/12OmNyS6RJo",
"parentPublication": {
"id": "proceedings/icdar/2011/4520/0",
"title": "2011 International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2022/9345/0/09852835",
"title": "Synthesizing Digital Libraries and Digital Humanities Perspectives for Illuminating Under-investigated Complexities associated with User-generated Book Reviews",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2022/09852835/1FT2poylLaw",
"parentPublication": {
"id": "proceedings/jcdl/2022/9345/0",
"title": "2022 ACM/IEEE Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904442",
"title": "Communicating Uncertainty in Digital Humanities Visualization Research",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904442/1H1gpt871W8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2022/7668/0/766800a013",
"title": "The Multiple Faces of Cultural Heritage: Towards an Integrated Visualization Platform for Tangible and Intangible Cultural Assets",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2022/766800a013/1J2XHjT07zq",
"parentPublication": {
"id": "proceedings/vis4dh/2022/7668/0",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2022/7668/0/766800a019",
"title": "Labeling of Cultural Heritage Collections on the Intersection of Visual Analytics and Digital Humanities",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2022/766800a019/1J2XI8P9aLe",
"parentPublication": {
"id": "proceedings/vis4dh/2022/7668/0",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/5555/01/10122138",
"title": "Science Gateways and the Humanities: An Exploratory Study of their Rare Partnership",
"doi": null,
"abstractUrl": "/magazine/cs/5555/01/10122138/1N0swfAXrcA",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2020/03/08999515",
"title": "A Data-Driven Introduction to Authors, Readings, and Techniques in Visualization for the Digital Humanities",
"doi": null,
"abstractUrl": "/magazine/cg/2020/03/08999515/1hpPHQ3jV7i",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2019/2284/0/08986953",
"title": "VIS Capstone Address: Visualizing Temporality and Chronologies for the Humanities",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2019/08986953/1ifhkTytY9a",
"parentPublication": {
"id": "proceedings/vast/2019/2284/0",
"title": "2019 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KBqPQkw71C",
"title": "2022 IEEE International Conference on Data Mining Workshops (ICDMW)",
"acronym": "icdmw",
"groupId": "10029378",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1KBr5pVl2qA",
"doi": "10.1109/ICDMW58026.2022.00086",
"title": "Unsupervised DeepView: Global Uncertainty Visualization for High Dimensional Data",
"normalizedTitle": "Unsupervised DeepView: Global Uncertainty Visualization for High Dimensional Data",
"abstract": "In recent years, more and more visualization methods for explanations of artificial intelligence have been proposed that focus on untangling black box models for single instances of the data set. While the focus often lies on supervised learning algorithms, the study of uncertainty estimations in the unsupervised domain for high-dimensional data sets in the explainability domain has been neglected so far. As a result, existing visualization methods struggle to visualize global uncertainty patterns over whole datasets. We propose Unsupervised DeepView, the first global uncertainty visualization method for high dimensional data based on a novel unsupervised proxy for local uncertainties. In this paper, we exploit the mathematical notion of local intrinsic dimensionality as a measure of local data complexity. As a label-agnostic measure of model uncertainty in unsupervised machine learning, it shows two highly desirable features: It can be used for global structure visualization as well as for the detection of local adversarials. In our empirical evaluation, we demonstrate its ability both in visualizations and quantitative analysis for unsupervised models on multiple datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In recent years, more and more visualization methods for explanations of artificial intelligence have been proposed that focus on untangling black box models for single instances of the data set. While the focus often lies on supervised learning algorithms, the study of uncertainty estimations in the unsupervised domain for high-dimensional data sets in the explainability domain has been neglected so far. As a result, existing visualization methods struggle to visualize global uncertainty patterns over whole datasets. We propose Unsupervised DeepView, the first global uncertainty visualization method for high dimensional data based on a novel unsupervised proxy for local uncertainties. In this paper, we exploit the mathematical notion of local intrinsic dimensionality as a measure of local data complexity. As a label-agnostic measure of model uncertainty in unsupervised machine learning, it shows two highly desirable features: It can be used for global structure visualization as well as for the detection of local adversarials. In our empirical evaluation, we demonstrate its ability both in visualizations and quantitative analysis for unsupervised models on multiple datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In recent years, more and more visualization methods for explanations of artificial intelligence have been proposed that focus on untangling black box models for single instances of the data set. While the focus often lies on supervised learning algorithms, the study of uncertainty estimations in the unsupervised domain for high-dimensional data sets in the explainability domain has been neglected so far. As a result, existing visualization methods struggle to visualize global uncertainty patterns over whole datasets. We propose Unsupervised DeepView, the first global uncertainty visualization method for high dimensional data based on a novel unsupervised proxy for local uncertainties. In this paper, we exploit the mathematical notion of local intrinsic dimensionality as a measure of local data complexity. As a label-agnostic measure of model uncertainty in unsupervised machine learning, it shows two highly desirable features: It can be used for global structure visualization as well as for the detection of local adversarials. In our empirical evaluation, we demonstrate its ability both in visualizations and quantitative analysis for unsupervised models on multiple datasets.",
"fno": "460900a626",
"keywords": [
"Artificial Intelligence",
"Data Visualisation",
"Learning Artificial Intelligence",
"Supervised Learning",
"Unsupervised Learning",
"Artificial Intelligence",
"Explainability Domain",
"Global Structure Visualization",
"Global Uncertainty Patterns",
"Global Uncertainty Visualization Method",
"High Dimensional Data",
"High Dimensional Data Sets",
"Highly Desirable Features",
"Local Data Complexity",
"Local Intrinsic Dimensionality",
"Local Uncertainties",
"Model Uncertainty",
"Novel Unsupervised Proxy",
"Single Instances",
"Supervised Learning Algorithms",
"Uncertainty Estimations",
"Unsupervised Deep View",
"Unsupervised Domain",
"Unsupervised Machine Learning",
"Unsupervised Models",
"Untangling Black Box Models",
"Visualization Methods Struggle",
"Uncertainty",
"Statistical Analysis",
"Supervised Learning",
"Measurement Uncertainty",
"Data Visualization",
"Estimation",
"Machine Learning",
"Visualization",
"Unsupervised Learning",
"Uncertainty Quantification",
"Adversarials"
],
"authors": [
{
"affiliation": "Research Center Trustworthy Data Science and Security,Dortmund,TU,Germany",
"fullName": "Carina Newen",
"givenName": "Carina",
"surname": "Newen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Research Center Trustworthy Data Science and Security,Dortmund,TU,Germany",
"fullName": "Emmanuel Müller",
"givenName": "Emmanuel",
"surname": "Müller",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdmw",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-11-01T00:00:00",
"pubType": "proceedings",
"pages": "1-8",
"year": "2022",
"issn": null,
"isbn": "979-8-3503-4609-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "460900a618",
"articleId": "1KBqTAdEZdm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "460900a634",
"articleId": "1KBr0gpxlM4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdm/2010/4256/0/4256a304",
"title": "Exploiting Local Data Uncertainty to Boost Global Outlier Detection",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2010/4256a304/12OmNBSSVbO",
"parentPublication": {
"id": "proceedings/icdm/2010/4256/0",
"title": "2010 IEEE International Conference on Data Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/1996/3673/0/36730189",
"title": "LISTEN: Sounding Uncertainty Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1996/36730189/12OmNqzu6Ua",
"parentPublication": {
"id": "proceedings/ieee-vis/1996/3673/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2013/01/mcg2013010075",
"title": "Visualization of Uncertainty without a Mean",
"doi": null,
"abstractUrl": "/magazine/cg/2013/01/mcg2013010075/13rRUwcAquB",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2008/01/ttg2008010061",
"title": "A Spreadsheet Approach to Facilitate Visualization of Uncertainty in Information",
"doi": null,
"abstractUrl": "/journal/tg/2008/01/ttg2008010061/13rRUxlgy3x",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/quatic/2018/5841/0/584100a238",
"title": "Uncertainty Management for Global Software Development Teams",
"doi": null,
"abstractUrl": "/proceedings-article/quatic/2018/584100a238/17D45WLdYPM",
"parentPublication": {
"id": "proceedings/quatic/2018/5841/0",
"title": "2018 11th International Conference on the Quality of Information and Communications Technology (QUATIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08457476",
"title": "In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08457476/17D45WaTkcP",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500b555",
"title": "Uncertainty Learning towards Unsupervised Deformable Medical Image Registration",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500b555/1B13zaPGj7y",
"parentPublication": {
"id": "proceedings/wacv/2022/0915/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ickg/2022/5101/0/510100a196",
"title": "Unsupervised DeepView: Global Explainability of Uncertainties for High Dimensional Data",
"doi": null,
"abstractUrl": "/proceedings-article/ickg/2022/510100a196/1KxU0VArAty",
"parentPublication": {
"id": "proceedings/ickg/2022/5101/0",
"title": "2022 IEEE International Conference on Knowledge Graph (ICKG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08794553",
"title": "A Structural Average of Labeled Merge Trees for Uncertainty Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08794553/1fe7uYD8R68",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2021/1370/0/137000a012",
"title": "Uncertainty-aware Topic Modeling Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2021/137000a012/1yNiG9yU9JS",
"parentPublication": {
"id": "proceedings/vis4dh/2021/1370/0",
"title": "2021 IEEE 6th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1pZ0XeP9TOw",
"title": "2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"acronym": "vis4dh",
"groupId": "1839705",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1pZ0XhtNffW",
"doi": "10.1109/VIS4DH51463.2020.00009",
"title": "Pilaster: A Collection of Citation Metadata Extracted From Publications on Visualization for the Digital Humanities",
"normalizedTitle": "Pilaster: A Collection of Citation Metadata Extracted From Publications on Visualization for the Digital Humanities",
"abstract": "In this paper, we present Pilaster (https://visusal.github.io/pilaster/), a collection of citation metadata extracted from publications in visualization for the digital humanities. The collection is generated from a seed set of relevant publications from which we extracted cited works, including journal and conference papers, books, theses, or blog posts, among other resources. The main aim of this work revolves around three main points: first, the collection may serve as an entry point to the discipline for digital humanists and visualization scholars without previous experience in the field. Second, Pilaster can be regarded as a meeting point for more established visualization or humanities scholars seeking to collaborate in the development of novel research ideas and related visualization design studies in the context of the humanities. Third, and given the large amount of visualization design spaces that were captured, we believe the dataset has the potential to become the starting point for future studies aimed at understanding the particularities of problem-driven visualization research in this and other contexts.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we present Pilaster (https://visusal.github.io/pilaster/), a collection of citation metadata extracted from publications in visualization for the digital humanities. The collection is generated from a seed set of relevant publications from which we extracted cited works, including journal and conference papers, books, theses, or blog posts, among other resources. The main aim of this work revolves around three main points: first, the collection may serve as an entry point to the discipline for digital humanists and visualization scholars without previous experience in the field. Second, Pilaster can be regarded as a meeting point for more established visualization or humanities scholars seeking to collaborate in the development of novel research ideas and related visualization design studies in the context of the humanities. Third, and given the large amount of visualization design spaces that were captured, we believe the dataset has the potential to become the starting point for future studies aimed at understanding the particularities of problem-driven visualization research in this and other contexts.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we present Pilaster (https://visusal.github.io/pilaster/), a collection of citation metadata extracted from publications in visualization for the digital humanities. The collection is generated from a seed set of relevant publications from which we extracted cited works, including journal and conference papers, books, theses, or blog posts, among other resources. The main aim of this work revolves around three main points: first, the collection may serve as an entry point to the discipline for digital humanists and visualization scholars without previous experience in the field. Second, Pilaster can be regarded as a meeting point for more established visualization or humanities scholars seeking to collaborate in the development of novel research ideas and related visualization design studies in the context of the humanities. Third, and given the large amount of visualization design spaces that were captured, we believe the dataset has the potential to become the starting point for future studies aimed at understanding the particularities of problem-driven visualization research in this and other contexts.",
"fno": "915300a024",
"keywords": [
"Citation Analysis",
"Data Visualisation",
"Humanities",
"Meta Data",
"Web Sites",
"Digital Humanists",
"Humanities Scholars",
"Visualization Design Spaces",
"Problem Driven Visualization Research",
"Citation Metadata",
"Digital Humanities",
"Pilaster",
"Data Visualization",
"Visualization",
"Metadata",
"Collaboration",
"Task Analysis",
"Organizations",
"Data Collection",
"Collaboration",
"Dataset",
"Digital Humanities",
"Visualization",
"Citation Analysis",
"Scientometrics"
],
"authors": [
{
"affiliation": "Universidad de Salamanca,VisUSAL Research Group,Spain",
"fullName": "Alejandro Benito-Santos",
"givenName": "Alejandro",
"surname": "Benito-Santos",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Universidad de Salamanca,VisUSAL Research Group,Spain",
"fullName": "Roberto Therón",
"givenName": "Roberto",
"surname": "Therón",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vis4dh",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-10-01T00:00:00",
"pubType": "proceedings",
"pages": "24-29",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-9153-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "915300a014",
"articleId": "1pZ0XkSYO1W",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "915300a030",
"articleId": "1pZ0XvrgcQE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/jcdl/2001/2287/0/22870426",
"title": "Building a Hypertextual Digital Library in the Humanities: A Case Study on London",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2001/22870426/12OmNyQGSoh",
"parentPublication": {
"id": "proceedings/jcdl/2001/2287/0",
"title": "Digital Libraries, Joint Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192666",
"title": "Speculative Practices: Utilizing InfoVis to Explore Untapped Literary Collections",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192666/13rRUB7a113",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192685",
"title": "CiteRivers: Visual Analytics of Citation Patterns",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192685/13rRUwd9CG5",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/09/07583708",
"title": "Vispubdata.org: A Metadata Collection About IEEE Visualization (VIS) Publications",
"doi": null,
"abstractUrl": "/journal/tg/2017/09/07583708/13rRUxd2aZ7",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2018/06/08617736",
"title": "Visualization and the Digital Humanities:",
"doi": null,
"abstractUrl": "/magazine/cg/2018/06/08617736/17D45Wuc32C",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904442",
"title": "Communicating Uncertainty in Digital Humanities Visualization Research",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904442/1H1gpt871W8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2022/7668/0/766800a019",
"title": "Labeling of Cultural Heritage Collections on the Intersection of Visual Analytics and Digital Humanities",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2022/766800a019/1J2XI8P9aLe",
"parentPublication": {
"id": "proceedings/vis4dh/2022/7668/0",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2019/1547/0/154700a138",
"title": "Modeling Digital Humanities Collections as Research Objects",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2019/154700a138/1ckrF3hMFyM",
"parentPublication": {
"id": "proceedings/jcdl/2019/1547/0",
"title": "2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2020/03/08999515",
"title": "A Data-Driven Introduction to Authors, Readings, and Techniques in Visualization for the Digital Humanities",
"doi": null,
"abstractUrl": "/magazine/cg/2020/03/08999515/1hpPHQ3jV7i",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2021/1770/0/177000a246",
"title": "Exploring the Classification of Traditional Chinese Bibliographies through Interactive Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2021/177000a246/1zJmYfHdJ7O",
"parentPublication": {
"id": "proceedings/jcdl/2021/1770/0",
"title": "2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzUPpvS",
"title": "Networks Security, Wireless Communications and Trusted Computing, International Conference on",
"acronym": "nswctc",
"groupId": "1002716",
"volume": "1",
"displayVolume": "1",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNARRYri",
"doi": "10.1109/NSWCTC.2009.55",
"title": "A Range Query Model Based on DHT in P2P System",
"normalizedTitle": "A Range Query Model Based on DHT in P2P System",
"abstract": "A Peer-to-Peer (P2P) system has emerged as one of the most successful ways to share resources in distributed environment, and DHT(Distributed Hash Table) is used as an effective approach to locate shared resources in a P2P system. This paper describes an extended DHT model by combining DHT with B+ tree. The sharing resources are represented by their attributes. Each query request is associated with ranges in one or more attributes, and B+ tree is introduced to organize the values of each attribute. In order to implement and verify our model, Chord is chosen as the underlying DHT system. In addition to equality queries, this model also makes it possible to execute range queries over a DHT. The relevant technologies mapping from B+ trees to Chord system are described. The node adding and leaving process and range query process are illustrated.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A Peer-to-Peer (P2P) system has emerged as one of the most successful ways to share resources in distributed environment, and DHT(Distributed Hash Table) is used as an effective approach to locate shared resources in a P2P system. This paper describes an extended DHT model by combining DHT with B+ tree. The sharing resources are represented by their attributes. Each query request is associated with ranges in one or more attributes, and B+ tree is introduced to organize the values of each attribute. In order to implement and verify our model, Chord is chosen as the underlying DHT system. In addition to equality queries, this model also makes it possible to execute range queries over a DHT. The relevant technologies mapping from B+ trees to Chord system are described. The node adding and leaving process and range query process are illustrated.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A Peer-to-Peer (P2P) system has emerged as one of the most successful ways to share resources in distributed environment, and DHT(Distributed Hash Table) is used as an effective approach to locate shared resources in a P2P system. This paper describes an extended DHT model by combining DHT with B+ tree. The sharing resources are represented by their attributes. Each query request is associated with ranges in one or more attributes, and B+ tree is introduced to organize the values of each attribute. In order to implement and verify our model, Chord is chosen as the underlying DHT system. In addition to equality queries, this model also makes it possible to execute range queries over a DHT. The relevant technologies mapping from B+ trees to Chord system are described. The node adding and leaving process and range query process are illustrated.",
"fno": "3610a670",
"keywords": [
"Peer To Peer",
"Query",
"DHT"
],
"authors": [
{
"affiliation": null,
"fullName": "Wang Dan",
"givenName": "Wang",
"surname": "Dan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Li Maozeng",
"givenName": "Li",
"surname": "Maozeng",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "nswctc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-04-01T00:00:00",
"pubType": "proceedings",
"pages": "670-674",
"year": "2009",
"issn": null,
"isbn": "978-0-7695-3610-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3610a666",
"articleId": "12OmNAle6C7",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3610a675",
"articleId": "12OmNzIUfS3",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cit/2009/3836/1/3836a051",
"title": "Yarqs: Yet Another Range Queries Schema in DHT Based P2P Network",
"doi": null,
"abstractUrl": "/proceedings-article/cit/2009/3836a051/12OmNApLGB3",
"parentPublication": {
"id": "proceedings/cit/2009/3836/1",
"title": "2009 Ninth IEEE International Conference on Computer and Information Technology. CIT 2009",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdcat/2011/4564/0/4564a152",
"title": "P2P DHT Based on a Contracted Star Graph",
"doi": null,
"abstractUrl": "/proceedings-article/pdcat/2011/4564a152/12OmNAtaRXu",
"parentPublication": {
"id": "proceedings/pdcat/2011/4564/0",
"title": "Parallel and Distributed Computing Applications and Technologies, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpp/2009/3802/0/3802a420",
"title": "SandStone: A DHT Based Carrier Grade Distributed Storage System",
"doi": null,
"abstractUrl": "/proceedings-article/icpp/2009/3802a420/12OmNBQ2W2Q",
"parentPublication": {
"id": "proceedings/icpp/2009/3802/0",
"title": "2009 International Conference on Parallel Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2008/3454/0/3454a348",
"title": "Pseudo-DHT: Distributed Search Algorithm for P2P Video Streaming",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2008/3454a348/12OmNBTs7oP",
"parentPublication": {
"id": "proceedings/ism/2008/3454/0",
"title": "2008 Tenth IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ifita/2009/3600/1/3600a626",
"title": "Efficient Range Indexing in DHT-Based Peer-to-Peer Networks",
"doi": null,
"abstractUrl": "/proceedings-article/ifita/2009/3600a626/12OmNBp52J9",
"parentPublication": {
"id": "proceedings/ifita/2009/3600/3",
"title": "Information Technology and Applications, International Forum on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scalcom-embeddedcom/2009/3825/0/3825a409",
"title": "A Range Query Technology for Structured P2P Network",
"doi": null,
"abstractUrl": "/proceedings-article/scalcom-embeddedcom/2009/3825a409/12OmNviZlpy",
"parentPublication": {
"id": "proceedings/scalcom-embeddedcom/2009/3825/0",
"title": "Scalable Computing and Communications; International Conference on Embedded Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/kse/2009/3846/0/3846a195",
"title": "Building a Low-latency, Proximity-aware DHT-Based P2P Network",
"doi": null,
"abstractUrl": "/proceedings-article/kse/2009/3846a195/12OmNxEBziq",
"parentPublication": {
"id": "proceedings/kse/2009/3846/0",
"title": "Knowledge and Systems Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2011/0680/0/05983953",
"title": "Robustness of a P2P community management system based on two-level hierarchical DHT overlays",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2011/05983953/12OmNyugyCn",
"parentPublication": {
"id": "proceedings/iscc/2011/0680/0",
"title": "2011 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccgrid/2009/3622/0/3622a180",
"title": "Range Query Using Learning-Aware RPS in DHT-Based Peer-to-Peer Networks",
"doi": null,
"abstractUrl": "/proceedings-article/ccgrid/2009/3622a180/12OmNzUgdgw",
"parentPublication": {
"id": "proceedings/ccgrid/2009/3622/0",
"title": "Cluster Computing and the Grid, IEEE International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/saint/2008/3297/0/3297a018",
"title": "DHT Network with Link Access Control Using a Social Network",
"doi": null,
"abstractUrl": "/proceedings-article/saint/2008/3297a018/12OmNzfXavl",
"parentPublication": {
"id": "proceedings/saint/2008/3297/0",
"title": "2008 International Symposium on Applications and the Internet",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1FwF6rOD2ec",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"acronym": "icde",
"groupId": "1000178",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1FwFGbGwm5O",
"doi": "10.1109/ICDE53745.2022.00111",
"title": "Fairness-Aware Range Queries for Selecting Unbiased Data",
"normalizedTitle": "Fairness-Aware Range Queries for Selecting Unbiased Data",
"abstract": "We are being constantly judged by automated decision systems that have been widely criticised for being discriminatory and unfair. Since an algorithm is only as good as the data it works with, biases in the data can significantly amplify unfairness issues. In this paper, we take initial steps towards integrating fairness conditions into database query processing and data management systems. Specifically, we focus on selection bias in range queries. We formally define the problem of fairness-aware range queries as obtaining a fair query which is most similar to the user's query. We propose a sub-linear time algorithm for single-predicate range queries and efficient algorithms for multi-predicate range queries. Our empirical evaluation on real and synthetic datasets confirms the effectiveness and efficiency of our proposal.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We are being constantly judged by automated decision systems that have been widely criticised for being discriminatory and unfair. Since an algorithm is only as good as the data it works with, biases in the data can significantly amplify unfairness issues. In this paper, we take initial steps towards integrating fairness conditions into database query processing and data management systems. Specifically, we focus on selection bias in range queries. We formally define the problem of fairness-aware range queries as obtaining a fair query which is most similar to the user's query. We propose a sub-linear time algorithm for single-predicate range queries and efficient algorithms for multi-predicate range queries. Our empirical evaluation on real and synthetic datasets confirms the effectiveness and efficiency of our proposal.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We are being constantly judged by automated decision systems that have been widely criticised for being discriminatory and unfair. Since an algorithm is only as good as the data it works with, biases in the data can significantly amplify unfairness issues. In this paper, we take initial steps towards integrating fairness conditions into database query processing and data management systems. Specifically, we focus on selection bias in range queries. We formally define the problem of fairness-aware range queries as obtaining a fair query which is most similar to the user's query. We propose a sub-linear time algorithm for single-predicate range queries and efficient algorithms for multi-predicate range queries. Our empirical evaluation on real and synthetic datasets confirms the effectiveness and efficiency of our proposal.",
"fno": "088300b423",
"keywords": [
"Computational Complexity",
"Graph Theory",
"Query Processing",
"Fairness Aware Range Queries",
"Unbiased Data",
"Automated Decision Systems",
"Database Query Processing",
"Data Management Systems",
"Fair Query",
"Single Predicate Range Queries",
"Multipredicate Range Queries",
"Sub Linear Time Algorithm",
"Databases",
"Query Processing",
"Conferences",
"Data Engineering",
"Proposals",
"Fair Databases",
"Data Bias",
"Algorithmic Fairness"
],
"authors": [
{
"affiliation": "University of Texas at Arlington",
"fullName": "Suraj Shetiya",
"givenName": "Suraj",
"surname": "Shetiya",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Illinois at Chicago",
"fullName": "Ian P. Swift",
"givenName": "Ian P.",
"surname": "Swift",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Illinois at Chicago",
"fullName": "Abolfazl Asudeh",
"givenName": "Abolfazl",
"surname": "Asudeh",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Texas at Arlington",
"fullName": "Gautam Das",
"givenName": "Gautam",
"surname": "Das",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icde",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-05-01T00:00:00",
"pubType": "proceedings",
"pages": "1423-1436",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-0883-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "088300b408",
"articleId": "1FwFbQPgUb6",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "088300b450",
"articleId": "1FwFwvBWbrG",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/compsac/1999/0368/0/03680350",
"title": "Processing Queries with Expensive Predicates by Filtering",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/1999/03680350/12OmNAndikS",
"parentPublication": {
"id": "proceedings/compsac/1999/0368/0",
"title": "Proceedings. Twenty-Third Annual International Computer Software and Applications Conference (Cat. No.99CB37032)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2009/4672/0/05202326",
"title": "Compact N-tree: an indexing structure for distance range queries",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2009/05202326/12OmNCgrD6b",
"parentPublication": {
"id": "proceedings/iscc/2009/4672/0",
"title": "2009 IEEE Symposium on Computers and Communications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/1995/6910/0/69100090",
"title": "Translation of object-oriented queries to relational queries",
"doi": null,
"abstractUrl": "/proceedings-article/icde/1995/69100090/12OmNx6g6qi",
"parentPublication": {
"id": "proceedings/icde/1995/6910/0",
"title": "Proceedings of the Eleventh International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2000/02/k0238",
"title": "Optimization and Evaluation of Disjunctive Queries",
"doi": null,
"abstractUrl": "/journal/tk/2000/02/k0238/13rRUwhHcR7",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2012/07/ttk2012071313",
"title": "Saturn: Range Queries, Load Balancing and Fault Tolerance in DHT Data Systems",
"doi": null,
"abstractUrl": "/journal/tk/2012/07/ttk2012071313/13rRUx0xPnl",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2017/2715/0/08257954",
"title": "Spatiotemporal range pattern queries on large-scale co-movement pattern datasets",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2017/08257954/17D45WYQJ80",
"parentPublication": {
"id": "proceedings/big-data/2017/2715/0",
"title": "2017 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300b927",
"title": "vChain+: Optimizing Verifiable Blockchain Boolean Range Queries",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300b927/1FwFJY1Oe08",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a433",
"title": "PRISM: Prefix-Sum based Range Queries Processing Method under Local Differential Privacy",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a433/1FwFKLDDBte",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300b487",
"title": "Efficient and Oblivious Query Processing for Range and kNN Queries (Extended Abstract)",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300b487/1FwFewDhETC",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300d106",
"title": "Subgraph Query Generation with Fairness and Diversity Constraints",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300d106/1FwFs16jZIY",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1FwF6rOD2ec",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"acronym": "icde",
"groupId": "1000178",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1FwFJY1Oe08",
"doi": "10.1109/ICDE53745.2022.00190",
"title": "vChain+: Optimizing Verifiable Blockchain Boolean Range Queries",
"normalizedTitle": "vChain+: Optimizing Verifiable Blockchain Boolean Range Queries",
"abstract": "Blockchain has recently gained massive attention thanks to the success of cryptocurrencies and decentralized applications. With immutability and tamper-resistance features, it can be seen as a promising secure database solution. To address the need of searches over blockchain databases, prior work vChain proposed a novel verifiable processing framework that ensures query integrity without maintaining a full copy of the blockchain database. It however suffers from several limitations, including linear-scan search performance in the worst case and impractical public key management. In this paper, we propose a new searchable blockchain system, vChain+, that supports efficient verifiable boolean range queries with additional features. Specifically, we propose a sliding window accumulator index to achieve efficient query processing even for the worst case. We also design an object registration index to enable practical public key management without compromising the security guarantee. To support richer queries, we employ optimal tree-based indexes to index both keywords and numerical attributes of the data objects. Several optimizations are also proposed to further improve the query performance. Security analysis and empirical study validate the robustness and performance improvement of the proposed system. Compared with vChain, vChain+ improves the query performance by up to 913x.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Blockchain has recently gained massive attention thanks to the success of cryptocurrencies and decentralized applications. With immutability and tamper-resistance features, it can be seen as a promising secure database solution. To address the need of searches over blockchain databases, prior work vChain proposed a novel verifiable processing framework that ensures query integrity without maintaining a full copy of the blockchain database. It however suffers from several limitations, including linear-scan search performance in the worst case and impractical public key management. In this paper, we propose a new searchable blockchain system, vChain+, that supports efficient verifiable boolean range queries with additional features. Specifically, we propose a sliding window accumulator index to achieve efficient query processing even for the worst case. We also design an object registration index to enable practical public key management without compromising the security guarantee. To support richer queries, we employ optimal tree-based indexes to index both keywords and numerical attributes of the data objects. Several optimizations are also proposed to further improve the query performance. Security analysis and empirical study validate the robustness and performance improvement of the proposed system. Compared with vChain, vChain+ improves the query performance by up to 913x.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Blockchain has recently gained massive attention thanks to the success of cryptocurrencies and decentralized applications. With immutability and tamper-resistance features, it can be seen as a promising secure database solution. To address the need of searches over blockchain databases, prior work vChain proposed a novel verifiable processing framework that ensures query integrity without maintaining a full copy of the blockchain database. It however suffers from several limitations, including linear-scan search performance in the worst case and impractical public key management. In this paper, we propose a new searchable blockchain system, vChain+, that supports efficient verifiable boolean range queries with additional features. Specifically, we propose a sliding window accumulator index to achieve efficient query processing even for the worst case. We also design an object registration index to enable practical public key management without compromising the security guarantee. To support richer queries, we employ optimal tree-based indexes to index both keywords and numerical attributes of the data objects. Several optimizations are also proposed to further improve the query performance. Security analysis and empirical study validate the robustness and performance improvement of the proposed system. Compared with vChain, vChain+ improves the query performance by up to 913x.",
"fno": "088300b927",
"keywords": [
"Blockchains",
"Public Key Cryptography",
"Query Processing",
"Tree Data Structures",
"Trees Mathematics",
"Blockchain Database",
"V Chain",
"Query Integrity",
"Linear Scan Search Performance",
"Searchable Blockchain System",
"Sliding Window Accumulator Index",
"Object Registration Index",
"Public Key Management",
"Security Guarantee",
"Tree Based Indexes",
"Query Performance",
"Security Analysis",
"Decentralized Applications",
"Tamper Resistance Features",
"Verifiable Blockchain Boolean Range Queries",
"Databases",
"Query Processing",
"Public Key",
"Decentralized Applications",
"Data Engineering",
"Robustness",
"Blockchains",
"Blockchain",
"Query Processing",
"Verifiable Computing",
"Integrity"
],
"authors": [
{
"affiliation": "Hong Kong Baptist University,Department of Computer Science,Hong Kong",
"fullName": "Haixin Wang",
"givenName": "Haixin",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hong Kong Baptist University,Department of Computer Science,Hong Kong",
"fullName": "Cheng Xu",
"givenName": "Cheng",
"surname": "Xu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hong Kong Baptist University,Department of Computer Science,Hong Kong",
"fullName": "Ce Zhang",
"givenName": "Ce",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hong Kong Baptist University,Department of Computer Science,Hong Kong",
"fullName": "Jianliang Xu",
"givenName": "Jianliang",
"surname": "Xu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hong Kong Baptist University,Department of Computer Science,Hong Kong",
"fullName": "Zhe Peng",
"givenName": "Zhe",
"surname": "Peng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Simon Fraser University,School of Computing Science,Canada",
"fullName": "Jian Pei",
"givenName": "Jian",
"surname": "Pei",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icde",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-05-01T00:00:00",
"pubType": "proceedings",
"pages": "1927-1940",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-0883-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "088300b914",
"articleId": "1FwFDDPyQjm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "088300b941",
"articleId": "1FwFCrRDsR2",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/blockchain/2021/1760/0/176000a160",
"title": "A Voting-Based Blockchain Interoperability Oracle",
"doi": null,
"abstractUrl": "/proceedings-article/blockchain/2021/176000a160/1AqxBNrKCqY",
"parentPublication": {
"id": "proceedings/blockchain/2021/1760/0",
"title": "2021 IEEE International Conference on Blockchain (Blockchain)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tq/5555/01/09772317",
"title": "Towards Public Verifiable and Forward-Privacy Encrypted Search by Using Blockchain",
"doi": null,
"abstractUrl": "/journal/tq/5555/01/09772317/1DgjGrHiZOM",
"parentPublication": {
"id": "trans/tq",
"title": "IEEE Transactions on Dependable and Secure Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/blockchain/2022/6104/0/610400a177",
"title": "Authenticated Multi-Version Index for Blockchain-based Range Queries on Historical Data",
"doi": null,
"abstractUrl": "/proceedings-article/blockchain/2022/610400a177/1GNt8rNHmV2",
"parentPublication": {
"id": "proceedings/blockchain/2022/6104/0",
"title": "2022 IEEE International Conference on Blockchain (Blockchain)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dapps/2022/9172/0/917200a074",
"title": "The DecCert PKI: A Solution to Decentralized Identity Attestation and Zooko’s Triangle",
"doi": null,
"abstractUrl": "/proceedings-article/dapps/2022/917200a074/1H0KtlI4oCI",
"parentPublication": {
"id": "proceedings/dapps/2022/9172/0",
"title": "2022 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09942353",
"title": "MSTDB: A Hybrid Storage-Empowered Scalable Semantic Blockchain Database",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09942353/1I8NKSHGtRm",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tq/5555/01/09980409",
"title": "ACA: Anonymous, Confidential and Auditable Transaction Systems for Blockchain",
"doi": null,
"abstractUrl": "/journal/tq/5555/01/09980409/1J2Ty06BW7K",
"parentPublication": {
"id": "trans/tq",
"title": "IEEE Transactions on Dependable and Secure Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/5555/01/09994615",
"title": "VRBC: A Verifiable Redactable Blockchain with Efficient Query and Integrity Auditing",
"doi": null,
"abstractUrl": "/journal/tc/5555/01/09994615/1Jgwdy67fzy",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2019/7474/0/747400a626",
"title": "ServeDB: Secure, Verifiable, and Efficient Range Queries on Outsourced Database",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2019/747400a626/1aDSTKhhiG4",
"parentPublication": {
"id": "proceedings/icde/2019/7474/0",
"title": "2019 IEEE 35th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dapps/2020/6978/0/09126007",
"title": "LBRY: A Blockchain-Based Decentralized Digital Content Marketplace",
"doi": null,
"abstractUrl": "/proceedings-article/dapps/2020/09126007/1liyOIrEA48",
"parentPublication": {
"id": "proceedings/dapps/2020/6978/0",
"title": "2020 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2022/06/09541060",
"title": "VQL: Efficient and Verifiable Cloud Query Services for Blockchain Systems",
"doi": null,
"abstractUrl": "/journal/td/2022/06/09541060/1x3fXxfGoog",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1xIOMBjN5EQ",
"title": "2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)",
"acronym": "ichi",
"groupId": "1803080",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1xIOV00mOQg",
"doi": "10.1109/ICHI52183.2021.00044",
"title": "Interactive Range Queries for Healthcare Data under Differential Privacy",
"normalizedTitle": "Interactive Range Queries for Healthcare Data under Differential Privacy",
"abstract": "Analyses of fine-grained healthcare data by medical researchers can have many societal benefits, including helping to track the spread of COVID-19 and treatment successes. As healthcare data includes personally identifying information (PII), privacy loss needs to be prevented. Differential privacy permits data analysis without loss of individual privacy via a curator who guards the data and determines its appropriate release. An Z_$\\in$_Z parameter measures the noise applied to the query results to control exposure of sensitive data: a low Z_$\\in$_Z value corresponds to more privacy protection, while a higher Z_$\\in$_Z value releases more accurate results with less privacy. Range queries, which count the number of values in a dataset within a user-defined range, pose privacy challenges that are especially concerning in healthcare applications. For example, an adversary can make sequential and overlapping range queries over a sensitive attribute, resulting in isolating information about a specific individual. This work addresses range query privacy concerns in the healthcare domain by proposing an Z_$\\epsilon$_Z-private Multi-Attribute DisAssembly Mechanism (MADAM). MADAM supports both single-attribute and multiattribute range queries involving sensitive attributes. The paper also presents BiMADAM, an extension that reduces the error to be polylogarithmic in the sensitivity degree of the queries.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Analyses of fine-grained healthcare data by medical researchers can have many societal benefits, including helping to track the spread of COVID-19 and treatment successes. As healthcare data includes personally identifying information (PII), privacy loss needs to be prevented. Differential privacy permits data analysis without loss of individual privacy via a curator who guards the data and determines its appropriate release. An $\\in$ parameter measures the noise applied to the query results to control exposure of sensitive data: a low $\\in$ value corresponds to more privacy protection, while a higher $\\in$ value releases more accurate results with less privacy. Range queries, which count the number of values in a dataset within a user-defined range, pose privacy challenges that are especially concerning in healthcare applications. For example, an adversary can make sequential and overlapping range queries over a sensitive attribute, resulting in isolating information about a specific individual. This work addresses range query privacy concerns in the healthcare domain by proposing an $\\epsilon$-private Multi-Attribute DisAssembly Mechanism (MADAM). MADAM supports both single-attribute and multiattribute range queries involving sensitive attributes. The paper also presents BiMADAM, an extension that reduces the error to be polylogarithmic in the sensitivity degree of the queries.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Analyses of fine-grained healthcare data by medical researchers can have many societal benefits, including helping to track the spread of COVID-19 and treatment successes. As healthcare data includes personally identifying information (PII), privacy loss needs to be prevented. Differential privacy permits data analysis without loss of individual privacy via a curator who guards the data and determines its appropriate release. An - parameter measures the noise applied to the query results to control exposure of sensitive data: a low - value corresponds to more privacy protection, while a higher - value releases more accurate results with less privacy. Range queries, which count the number of values in a dataset within a user-defined range, pose privacy challenges that are especially concerning in healthcare applications. For example, an adversary can make sequential and overlapping range queries over a sensitive attribute, resulting in isolating information about a specific individual. This work addresses range query privacy concerns in the healthcare domain by proposing an --private Multi-Attribute DisAssembly Mechanism (MADAM). MADAM supports both single-attribute and multiattribute range queries involving sensitive attributes. The paper also presents BiMADAM, an extension that reduces the error to be polylogarithmic in the sensitivity degree of the queries.",
"fno": "013200a228",
"keywords": [
"Data Analysis",
"Data Privacy",
"Health Care",
"Medical Information Systems",
"Query Processing",
"Privacy Challenges",
"Healthcare Applications",
"Sequential Range Queries",
"Overlapping Range Queries",
"Sensitive Attribute",
"Range Query Privacy Concerns",
"Healthcare Domain",
"Multiattribute Range Queries",
"Interactive Range Queries",
"Differential Privacy",
"Fine Grained Healthcare Data",
"Medical Researchers",
"Societal Benefits",
"COVID 19",
"Privacy Loss",
"Data Analysis",
"Individual Privacy",
"Privacy Protection",
"User Defined Range",
"Multiattribute Disassembly Mechanism",
"COVID 19",
"Differential Privacy",
"Privacy",
"Sensitivity",
"Pandemics",
"Medical Services",
"Vaccines",
"Healthcare Data",
"Data Privacy",
"Differential Privacy",
"Data Analytics"
],
"authors": [
{
"affiliation": "Taif University,College of Computers and Information Technology,Taif,Saudi Arabia,26571",
"fullName": "Asma Alnemari",
"givenName": "Asma",
"surname": "Alnemari",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rochester Institute of Technology,Golisano College of Computing and Information Sciences,Rochester,NY,USA,14623",
"fullName": "Rajendra K. Raj",
"givenName": "Rajendra K.",
"surname": "Raj",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rochester Institute of Technology,Golisano College of Computing and Information Sciences,Rochester,NY,USA,14623",
"fullName": "Carol J. Romanowski",
"givenName": "Carol J.",
"surname": "Romanowski",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rochester Institute of Technology,Golisano College of Computing and Information Sciences,Rochester,NY,USA,14623",
"fullName": "Sumita Mishra",
"givenName": "Sumita",
"surname": "Mishra",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ichi",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-08-01T00:00:00",
"pubType": "proceedings",
"pages": "228-237",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-0132-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "013200a224",
"articleId": "1xIOWmcq4SI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "013200a238",
"articleId": "1xIOVJdpGjm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ichi/2017/4881/0/4881a397",
"title": "An Adaptive Differential Privacy Algorithm for Range Queries over Healthcare Data",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2017/4881a397/12OmNs4S8Hl",
"parentPublication": {
"id": "proceedings/ichi/2017/4881/0",
"title": "2017 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2011/08/ttk2011081200",
"title": "Differential Privacy via Wavelet Transforms",
"doi": null,
"abstractUrl": "/journal/tk/2011/08/ttk2011081200/13rRUxOdD8B",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/it/2022/01/09717336",
"title": "iTrace: When IOTA Meets COVID-19 Contact Tracing",
"doi": null,
"abstractUrl": "/magazine/it/2022/01/09717336/1BaW3h0sFLW",
"parentPublication": {
"id": "mags/it",
"title": "IT Professional",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tq/5555/01/09767631",
"title": "Achieving Privacy-Preserving Discrete Frchet Distance Range Queries",
"doi": null,
"abstractUrl": "/journal/tq/5555/01/09767631/1D4SeReVxqU",
"parentPublication": {
"id": "trans/tq",
"title": "IEEE Transactions on Dependable and Secure Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbd/2022/0745/0/074500a230",
"title": "Non-Interactive Correlation Differential Privacy for Healthcare Data",
"doi": null,
"abstractUrl": "/proceedings-article/cbd/2022/074500a230/1EVipVzCScw",
"parentPublication": {
"id": "proceedings/cbd/2022/0745/0",
"title": "2021 Ninth International Conference on Advanced Cloud and Big Data (CBD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a433",
"title": "PRISM: Prefix-Sum based Range Queries Processing Method under Local Differential Privacy",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a433/1FwFKLDDBte",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccri/2022/6800/0/680000a088",
"title": "Analysis and Improvement in Healthcare Operation Utilizing Automation",
"doi": null,
"abstractUrl": "/proceedings-article/iccri/2022/680000a088/1GlfZAiiSqc",
"parentPublication": {
"id": "proceedings/iccri/2022/6800/0",
"title": "2022 International Conference on Control, Robotics and Informatics (ICCRI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cogmi/2022/7406/0/740600a059",
"title": "PSLotto: A Privacy-Enhanced COVID Lottery System",
"doi": null,
"abstractUrl": "/proceedings-article/cogmi/2022/740600a059/1Lu4jFHTTaw",
"parentPublication": {
"id": "proceedings/cogmi/2022/7406/0",
"title": "2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2020/8086/0/09219739",
"title": "Power Range: Forward Private Multi-Client Symmetric Searchable Encryption with Range Queries Support",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2020/09219739/1nRPgmrMnfi",
"parentPublication": {
"id": "proceedings/iscc/2020/8086/0",
"title": "2020 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2021/2463/0/246300b351",
"title": "Cybersecurity Risks and Mitigation Techniques During COVID-19",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2021/246300b351/1wLctnvHMyc",
"parentPublication": {
"id": "proceedings/compsac/2021/2463/0",
"title": "2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1cMF8oE0kI8",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1cMFaLfxpU4",
"doi": "10.1109/IV.2019.00016",
"title": "Analyzing the Effect of Different Partial Overlap Sizes in Perceiving Visual Variables",
"normalizedTitle": "Analyzing the Effect of Different Partial Overlap Sizes in Perceiving Visual Variables",
"abstract": "Element overlap in visualization techniques is a known problem, and high amounts of data and lack of available visual space potentialize this issue. Many studies have applied techniques to reduce occlusion levels in data visualizations, such as random jitter, element transparency, layout rearrangement, and focus+context techniques. However, few studies focus on the presence of occlusion, which is a relevant topic for visualizations where some degree of overlap is inevitable or purposefully explored. This paper takes a step in this direction, and presents a comparative study of visual variables, measuring their robustness to overlap and number of unique values. The study used a grid layout to display visual variables (hue, saturation, shape, text, orientation, and texture), and varied percentage of occlusion (0%, 50%, 60% and 70%) and number of unique values (3, 4 and 5) to measure the effect they cause on the speed and accuracy to locate the visual variables. Hence, 48 volunteers performed locate tasks on a tool that automatically generate a grid of visual variables and collect their answers. The results revealed that hue and shape were robust to high occlusion levels and a high number of unique values. Text and texture had medium loss of performance, while saturation and orientation were the most negatively affected.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Element overlap in visualization techniques is a known problem, and high amounts of data and lack of available visual space potentialize this issue. Many studies have applied techniques to reduce occlusion levels in data visualizations, such as random jitter, element transparency, layout rearrangement, and focus+context techniques. However, few studies focus on the presence of occlusion, which is a relevant topic for visualizations where some degree of overlap is inevitable or purposefully explored. This paper takes a step in this direction, and presents a comparative study of visual variables, measuring their robustness to overlap and number of unique values. The study used a grid layout to display visual variables (hue, saturation, shape, text, orientation, and texture), and varied percentage of occlusion (0%, 50%, 60% and 70%) and number of unique values (3, 4 and 5) to measure the effect they cause on the speed and accuracy to locate the visual variables. Hence, 48 volunteers performed locate tasks on a tool that automatically generate a grid of visual variables and collect their answers. The results revealed that hue and shape were robust to high occlusion levels and a high number of unique values. Text and texture had medium loss of performance, while saturation and orientation were the most negatively affected.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Element overlap in visualization techniques is a known problem, and high amounts of data and lack of available visual space potentialize this issue. Many studies have applied techniques to reduce occlusion levels in data visualizations, such as random jitter, element transparency, layout rearrangement, and focus+context techniques. However, few studies focus on the presence of occlusion, which is a relevant topic for visualizations where some degree of overlap is inevitable or purposefully explored. This paper takes a step in this direction, and presents a comparative study of visual variables, measuring their robustness to overlap and number of unique values. The study used a grid layout to display visual variables (hue, saturation, shape, text, orientation, and texture), and varied percentage of occlusion (0%, 50%, 60% and 70%) and number of unique values (3, 4 and 5) to measure the effect they cause on the speed and accuracy to locate the visual variables. Hence, 48 volunteers performed locate tasks on a tool that automatically generate a grid of visual variables and collect their answers. The results revealed that hue and shape were robust to high occlusion levels and a high number of unique values. Text and texture had medium loss of performance, while saturation and orientation were the most negatively affected.",
"fno": "283800a037",
"keywords": [
"Data Visualisation",
"Perceiving Visual",
"Visualization Techniques",
"Data Visualizations",
"Focus Context Techniques",
"Visual Variables",
"Overlap Number",
"Visual Space",
"Occlusion Levels",
"Partial Overlap Sizes",
"Visualization",
"Data Visualization",
"Shape",
"Task Analysis",
"Image Color Analysis",
"Tools",
"Layout",
"Evaluation Visual Variables Overlap Occlusion"
],
"authors": [
{
"affiliation": "Universidade Federal do Para",
"fullName": "Diego Hortencio dos Santos",
"givenName": "Diego Hortencio",
"surname": "dos Santos",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Universidade Federal do Para",
"fullName": "Anderson Gregório Marques Soares",
"givenName": "Anderson Gregório",
"surname": "Marques Soares",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Universidade Federal do Para",
"fullName": "Rodrigo Santos do Amor Divino Lima",
"givenName": "Rodrigo Santos",
"surname": "do Amor Divino Lima",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Universidade Federal do Para",
"fullName": "Elvis Thermo Carvalho Miranda",
"givenName": "Elvis Thermo Carvalho",
"surname": "Miranda",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Universidade Federal do Para",
"fullName": "Carlos Gustavo Resque dos Santos",
"givenName": "Carlos Gustavo Resque",
"surname": "dos Santos",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Universidade Federal do Para",
"fullName": "Bianchi Serique Meiguins",
"givenName": "Bianchi Serique",
"surname": "Meiguins",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-07-01T00:00:00",
"pubType": "proceedings",
"pages": "37-43",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-2838-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "283800z018",
"articleId": "1cMFbXMnsmk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "283800z019",
"articleId": "1cMFbaUOH5K",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/compsym/2016/3438/0/07858504",
"title": "An Efficient De-Overlap Algorithm for PCB Layout Patterns with Circular-Arc",
"doi": null,
"abstractUrl": "/proceedings-article/compsym/2016/07858504/12OmNvCzFdu",
"parentPublication": {
"id": "proceedings/compsym/2016/3438/0",
"title": "2016 International Computer Symposium (ICS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlhcc/2013/0369/0/06645262",
"title": "Improving user comprehension of Euler diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/vlhcc/2013/06645262/12OmNxveNOL",
"parentPublication": {
"id": "proceedings/vlhcc/2013/0369/0",
"title": "2013 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2015/10/07089294",
"title": "Representing Uncertainty in Graph Edges: An Evaluation of Paired Visual Variables",
"doi": null,
"abstractUrl": "/journal/tg/2015/10/07089294/13rRUxjyX42",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875950",
"title": "Learning Perceptual Kernels for Visualization Design",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875950/13rRUy3xY2S",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a058",
"title": "Visualizing Multidimensional Data in Treemaps with Adaptive Glyphs",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a058/17D45XeKgvR",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/01/09705149",
"title": "STORM: Structure-Based Overlap Matching for Partial Point Cloud Registration",
"doi": null,
"abstractUrl": "/journal/tp/2023/01/09705149/1AII6wed0Bi",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09925049",
"title": "Dual Space Coupling Model Guided Overlap-Free Scatterplot",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09925049/1HBHYSHqD3a",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2022/6814/0/681400a122",
"title": "An Extended Scatterplot Selection Technique for Representing Three Numeric Variables",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a122/1I6RMxpWlLG",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2018/8497/0/849700a028",
"title": "Preliminary Exploration of Three-Dimensional Visual Variables in Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2018/849700a028/1a3x79BSnkc",
"parentPublication": {
"id": "proceedings/icvrv/2018/8497/0",
"title": "2018 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2019/4941/0/08933606",
"title": "Overlap-Free Drawing of Generalized Pythagoras Trees for Hierarchy Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2019/08933606/1fTgJHbs9pu",
"parentPublication": {
"id": "proceedings/vis/2019/4941/0",
"title": "2019 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxX3uMV",
"title": "2011 Frontiers in Education Conference (FIE)",
"acronym": "fie",
"groupId": "1000297",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNy7h354",
"doi": "10.1109/FIE.2011.6142781",
"title": "A comprehensive project utilizing spatial visualization skills",
"normalizedTitle": "A comprehensive project utilizing spatial visualization skills",
"abstract": "It has been shown that spatial visualization skills are a critical part of engineering education. Methods to improve these skills are varied, but in general contain activities that have students attempt to visualize objects when translated or rotated from their original orientation. At Michigan Technological University, students take a two-semester engineering course sequence (ENG1101 and ENG1102) during their first year. Both courses have activities that help develop spatial visualization skills through hand sketching and 3D modeling. This paper describes two culminating spatial visualization activities that combine all the skills learned by the students in their engineering coursework. In one case, students are provided with an object that has four or more distinct parts. Students measure, sketch, dimension, and model a single component and then combine their object with their team member's objects into a completed assembly in NX. A more advanced boot dryer project allows students flexibility in their final design. Students are provided with several components to the dryer, but not all. Based on their measurements and models of the given parts, they can design and model unique boot dryer systems.",
"abstracts": [
{
"abstractType": "Regular",
"content": "It has been shown that spatial visualization skills are a critical part of engineering education. Methods to improve these skills are varied, but in general contain activities that have students attempt to visualize objects when translated or rotated from their original orientation. At Michigan Technological University, students take a two-semester engineering course sequence (ENG1101 and ENG1102) during their first year. Both courses have activities that help develop spatial visualization skills through hand sketching and 3D modeling. This paper describes two culminating spatial visualization activities that combine all the skills learned by the students in their engineering coursework. In one case, students are provided with an object that has four or more distinct parts. Students measure, sketch, dimension, and model a single component and then combine their object with their team member's objects into a completed assembly in NX. A more advanced boot dryer project allows students flexibility in their final design. Students are provided with several components to the dryer, but not all. Based on their measurements and models of the given parts, they can design and model unique boot dryer systems.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "It has been shown that spatial visualization skills are a critical part of engineering education. Methods to improve these skills are varied, but in general contain activities that have students attempt to visualize objects when translated or rotated from their original orientation. At Michigan Technological University, students take a two-semester engineering course sequence (ENG1101 and ENG1102) during their first year. Both courses have activities that help develop spatial visualization skills through hand sketching and 3D modeling. This paper describes two culminating spatial visualization activities that combine all the skills learned by the students in their engineering coursework. In one case, students are provided with an object that has four or more distinct parts. Students measure, sketch, dimension, and model a single component and then combine their object with their team member's objects into a completed assembly in NX. A more advanced boot dryer project allows students flexibility in their final design. Students are provided with several components to the dryer, but not all. Based on their measurements and models of the given parts, they can design and model unique boot dryer systems.",
"fno": "06142781",
"keywords": [
"Data Visualisation",
"Educational Courses",
"Engineering Education",
"Comprehensive Project Utilization",
"Spatial Visualization Skills",
"Engineering Education",
"Engineering Course",
"3 D Modeling",
"Hand Sketching",
"Engineering Coursework",
"Boot Dryer Systems",
"Visualization",
"Solid Modeling",
"Materials",
"Educational Institutions",
"Fitting",
"3 D Solid Modeling",
"First Year Engineering",
"Spatial Visualization"
],
"authors": [
{
"affiliation": "Michigan Technological University",
"fullName": "Amber Kemppainen",
"givenName": "Amber",
"surname": "Kemppainen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Michigan Technological University",
"fullName": "Brett Hamlin",
"givenName": "Brett",
"surname": "Hamlin",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "fie",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2011-10-01T00:00:00",
"pubType": "proceedings",
"pages": "S1C-1-S1C-5",
"year": "2011",
"issn": "0190-5848",
"isbn": "978-1-61284-468-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06142780",
"articleId": "12OmNs0TKKq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06142782",
"articleId": "12OmNy50g2v",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fie/2013/5261/0/06684827",
"title": "Student beliefs about learning communication skills",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2013/06684827/12OmNASraGj",
"parentPublication": {
"id": "proceedings/fie/2013/5261/0",
"title": "2013 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2013/5261/0/06684828",
"title": "Professional communication skills for engineering professionals",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2013/06684828/12OmNAXxXbD",
"parentPublication": {
"id": "proceedings/fie/2013/5261/0",
"title": "2013 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2014/3922/0/07044018",
"title": "A comprehensive engineering college-wide program for developing technical communication skills in students",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2014/07044018/12OmNBgQFH0",
"parentPublication": {
"id": "proceedings/fie/2014/3922/0",
"title": "2014 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2014/3922/0/07044161",
"title": "Empowering early mastery of spatial visualization skills in under represented minority engineering students",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2014/07044161/12OmNqGiu0a",
"parentPublication": {
"id": "proceedings/fie/2014/3922/0",
"title": "2014 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicis/2011/1561/0/06063219",
"title": "Experimental Analysis on Spiral Pressure Nozzle and Spray Angle Control in the Spray Dryer",
"doi": null,
"abstractUrl": "/proceedings-article/icicis/2011/06063219/12OmNwoPtp1",
"parentPublication": {
"id": "proceedings/icicis/2011/1561/0",
"title": "2011 International Conference on Internet Computing and Information Services (ICICIS 2011)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2014/3922/0/07044005",
"title": "Spatial skills as predictors of success in first-year engineering",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2014/07044005/12OmNwsNRdu",
"parentPublication": {
"id": "proceedings/fie/2014/3922/0",
"title": "2014 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2005/9077/0/01612135",
"title": "Learning project management skills in senior design courses",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2005/01612135/12OmNxTmHL7",
"parentPublication": {
"id": "proceedings/fie/2005/9077/0",
"title": "35th Annual Frontiers in Education",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/reet/2011/0954/0/06046272",
"title": "Final year project: A test case for requirements engineering skills",
"doi": null,
"abstractUrl": "/proceedings-article/reet/2011/06046272/12OmNxdVgKH",
"parentPublication": {
"id": "proceedings/reet/2011/0954/0",
"title": "2011 6th International Workshop on Requirements Engineering Education and Training",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2011/468/0/06142796",
"title": "Introducing “Sustainability and Social Commitment” skills in an engineering degree",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2011/06142796/12OmNyNzhsC",
"parentPublication": {
"id": "proceedings/fie/2011/468/0",
"title": "2011 Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2014/3922/0/07044179",
"title": "Improving communication skills: Students' viewpoint on a content & language integrated learning project",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2014/07044179/12OmNyQ7FMs",
"parentPublication": {
"id": "proceedings/fie/2014/3922/0",
"title": "2014 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNwbcJ3u",
"title": "Computing, Control and Industrial Engineering, International Conference on",
"acronym": "ccie",
"groupId": "1800073",
"volume": "2",
"displayVolume": "2",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzBOhXD",
"doi": "10.1109/CCIE.2010.157",
"title": "Application of Visualization Technology in Spatial Data Mining",
"normalizedTitle": "Application of Visualization Technology in Spatial Data Mining",
"abstract": "Spatial data mining and spatial data visualization are two comparatively popular technical methods in recent years, in essence, both purpose is to find geography phenomena what spatial data express and find various knowledge and laws implicit in geography entity. so it is necessary to combine both organically and form a new research direction - Visualization Spatial Data Mining (VSDM). This paper mainly discusses the key relationships of visualization and spatial data mining, the main Application of visualization theories and technologies in spatial data mining, the main methods and examples of visualization spatial data mining, we also present a reference model Visualization Spatial Data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Spatial data mining and spatial data visualization are two comparatively popular technical methods in recent years, in essence, both purpose is to find geography phenomena what spatial data express and find various knowledge and laws implicit in geography entity. so it is necessary to combine both organically and form a new research direction - Visualization Spatial Data Mining (VSDM). This paper mainly discusses the key relationships of visualization and spatial data mining, the main Application of visualization theories and technologies in spatial data mining, the main methods and examples of visualization spatial data mining, we also present a reference model Visualization Spatial Data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Spatial data mining and spatial data visualization are two comparatively popular technical methods in recent years, in essence, both purpose is to find geography phenomena what spatial data express and find various knowledge and laws implicit in geography entity. so it is necessary to combine both organically and form a new research direction - Visualization Spatial Data Mining (VSDM). This paper mainly discusses the key relationships of visualization and spatial data mining, the main Application of visualization theories and technologies in spatial data mining, the main methods and examples of visualization spatial data mining, we also present a reference model Visualization Spatial Data.",
"fno": "4026b153",
"keywords": [
"Visualization",
"Spatial Data Mining",
"Visualization Spatial Data Mining",
"Reference Model"
],
"authors": [
{
"affiliation": null,
"fullName": "Xiao Qiang",
"givenName": "Xiao",
"surname": "Qiang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Yan Wei",
"givenName": "Yan",
"surname": "Wei",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Zhang Hanfei",
"givenName": "Zhang",
"surname": "Hanfei",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ccie",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-06-01T00:00:00",
"pubType": "proceedings",
"pages": "153-157",
"year": "2010",
"issn": null,
"isbn": "978-0-7695-4026-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4026b149",
"articleId": "12OmNqzu6NE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4026b158",
"articleId": "12OmNzC5SMb",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ettandgrs/2008/3563/2/3563b541",
"title": "Spatial Data Mining Features between General Data Mining",
"doi": null,
"abstractUrl": "/proceedings-article/ettandgrs/2008/3563b541/12OmNA0MZ78",
"parentPublication": {
"id": "ettandgrs/2008/3563/2",
"title": "Education Technology and Training & Geoscience and Remote Sensing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wkdd/2009/3543/0/3543a159",
"title": "Research of GIS-based Spatial Data Mining Model",
"doi": null,
"abstractUrl": "/proceedings-article/wkdd/2009/3543a159/12OmNAmE5XM",
"parentPublication": {
"id": "proceedings/wkdd/2009/3543/0",
"title": "2009 Second International Workshop on Knowledge Discovery and Data Mining. WKDD 2009",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etcs/2009/3557/1/3557a133",
"title": "Visualized Spatial Data Classifying Based on Spatial Data Mining",
"doi": null,
"abstractUrl": "/proceedings-article/etcs/2009/3557a133/12OmNC4O4Fe",
"parentPublication": {
"id": "proceedings/etcs/2009/3557/2",
"title": "Education Technology and Computer Science, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2010/4256/0/4256b217",
"title": "Spatial and Spatio-temporal Data Mining",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2010/4256b217/12OmNCgrDcQ",
"parentPublication": {
"id": "proceedings/icdm/2010/4256/0",
"title": "2010 IEEE International Conference on Data Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/grc/2011/0372/0/06122686",
"title": "Spatial data mining under Smart Earth",
"doi": null,
"abstractUrl": "/proceedings-article/grc/2011/06122686/12OmNwfb6T4",
"parentPublication": {
"id": "proceedings/grc/2011/0372/0",
"title": "2011 IEEE International Conference on Granular Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/geoprocessing/2010/3951/0/3951a080",
"title": "Distributed Spatial Data Mining in Geospatial Knowledge Service Grid",
"doi": null,
"abstractUrl": "/proceedings-article/geoprocessing/2010/3951a080/12OmNwwMeZJ",
"parentPublication": {
"id": "proceedings/geoprocessing/2010/3951/0",
"title": "2010 Second International Conference on Advanced Geographic Information Systems, Applications, and Services",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2008/3357/2/3357c767",
"title": "The Application of Visualization Technology on Knowledge Management",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2008/3357c767/12OmNzFv4hI",
"parentPublication": {
"id": "icicta/2008/3357/2",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2015/7644/0/7644a702",
"title": "Research on Application of Visualized Data Mining Technology",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2015/7644a702/12OmNzl3WQO",
"parentPublication": {
"id": "proceedings/icicta/2015/7644/0",
"title": "2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2000/05/k0715",
"title": "An Approach to Active Spatial Data Mining Based on Statistical Information",
"doi": null,
"abstractUrl": "/journal/tk/2000/05/k0715/13rRUxYrbMA",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2021/3827/0/382700a223",
"title": "A Taxonomy of Spatial-Temporal Data Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2021/382700a223/1y4oJ9f6FuU",
"parentPublication": {
"id": "proceedings/iv/2021/3827/0",
"title": "2021 25th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1IHnB5FtCQ8",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"acronym": "fie",
"groupId": "1000297",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1IHo32fS0dq",
"doi": "10.1109/FIE56618.2022.9962621",
"title": "The Relationship Between Spatial Skills and Sketch Quality in Solving Problems in Engineering Mechanics",
"normalizedTitle": "The Relationship Between Spatial Skills and Sketch Quality in Solving Problems in Engineering Mechanics",
"abstract": "Spatial visualization is the ability to imagine what an object looks like from various viewpoints or after the object has been rotated in space by some amount. Numerous studies have shown the link between spatial skills and success in engineering. But how do well-developed spatial skills contribute to engineering student success? In studies with elementary students, children with good spatial skills were able to create schematic sketches—sketches that aided in the solution of the given problem. Poor visualizers drew pictorial sketches—those that did not help the student then solve the problem. A pilot study was conducted to determine the link between spatial skills and the ability to solve problems from engineering mechanics. In this study, a total of 47 students from upper division mechanical engineering courses completed a test of spatial skills and were also asked to solve 5-6 problems from introductory statics/physics. Results showed that a statistically significant positive correlation was found between spatial scores and the percent correct on the mechanics test. In this paper, we examine the quality of the sketches made by students while they were solving the problems and categorize them as either schematic or pictorial. Examination of the spatial skill levels of students who make schematic sketches will be compared to the spatial skill levels of those who make pictorial sketches.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Spatial visualization is the ability to imagine what an object looks like from various viewpoints or after the object has been rotated in space by some amount. Numerous studies have shown the link between spatial skills and success in engineering. But how do well-developed spatial skills contribute to engineering student success? In studies with elementary students, children with good spatial skills were able to create schematic sketches—sketches that aided in the solution of the given problem. Poor visualizers drew pictorial sketches—those that did not help the student then solve the problem. A pilot study was conducted to determine the link between spatial skills and the ability to solve problems from engineering mechanics. In this study, a total of 47 students from upper division mechanical engineering courses completed a test of spatial skills and were also asked to solve 5-6 problems from introductory statics/physics. Results showed that a statistically significant positive correlation was found between spatial scores and the percent correct on the mechanics test. In this paper, we examine the quality of the sketches made by students while they were solving the problems and categorize them as either schematic or pictorial. Examination of the spatial skill levels of students who make schematic sketches will be compared to the spatial skill levels of those who make pictorial sketches.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Spatial visualization is the ability to imagine what an object looks like from various viewpoints or after the object has been rotated in space by some amount. Numerous studies have shown the link between spatial skills and success in engineering. But how do well-developed spatial skills contribute to engineering student success? In studies with elementary students, children with good spatial skills were able to create schematic sketches—sketches that aided in the solution of the given problem. Poor visualizers drew pictorial sketches—those that did not help the student then solve the problem. A pilot study was conducted to determine the link between spatial skills and the ability to solve problems from engineering mechanics. In this study, a total of 47 students from upper division mechanical engineering courses completed a test of spatial skills and were also asked to solve 5-6 problems from introductory statics/physics. Results showed that a statistically significant positive correlation was found between spatial scores and the percent correct on the mechanics test. In this paper, we examine the quality of the sketches made by students while they were solving the problems and categorize them as either schematic or pictorial. Examination of the spatial skill levels of students who make schematic sketches will be compared to the spatial skill levels of those who make pictorial sketches.",
"fno": "09962621",
"keywords": [
"Computer Aided Instruction",
"Data Visualisation",
"Educational Courses",
"Engineering Education",
"Mechanical Engineering Computing",
"Engineering Mechanics",
"Engineering Student Success",
"Mechanics Test",
"Schematic Sketches",
"Spatial Scores",
"Spatial Skill Levels",
"Spatial Visualization",
"Upper Division Mechanical Engineering Courses",
"Visualization",
"Correlation",
"Psychology",
"Cognitive Load",
"Problem Solving",
"Mechanical Engineering",
"Engineering Students",
"Spatial Cognition",
"Problem Solving",
"Graphics",
"Sketching"
],
"authors": [
{
"affiliation": "University of Cincinnati,Department of Engineering Education,Cincinnati,OH,USA",
"fullName": "Sheryl Sorby",
"givenName": "Sheryl",
"surname": "Sorby",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Technological University Dublin,Electrical Engineering,Dublin,Ireland",
"fullName": "Gavin Duffy",
"givenName": "Gavin",
"surname": "Duffy",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Cincinnati,Department of Engineering Education,Cincinnati,OH,USA",
"fullName": "Sylvie Vieau",
"givenName": "Sylvie",
"surname": "Vieau",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "fie",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-5",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6244-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09962599",
"articleId": "1IHo4gQrxcI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09962407",
"articleId": "1IHot4VlPr2",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fie/2015/8454/0/07344341",
"title": "Systems thinking skills of undergraduate engineering students",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2015/07344341/12OmNAY79c8",
"parentPublication": {
"id": "proceedings/fie/2015/8454/0",
"title": "2015 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2016/1790/0/07757593",
"title": "Exploring the role of spatial cognition in problem solving",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2016/07757593/12OmNAnuTDC",
"parentPublication": {
"id": "proceedings/fie/2016/1790/0",
"title": "2016 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2013/5261/0/06684964",
"title": "Ill-structured problem solving in a workplace simulation environment: Challenges of the learning experience and skills developed",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2013/06684964/12OmNBqv2q8",
"parentPublication": {
"id": "proceedings/fie/2013/5261/0",
"title": "2013 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2012/1353/0/06462454",
"title": "Helping engineering students develop skills in content-based problem solving workshops outside classrooms",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2012/06462454/12OmNrFBQ0r",
"parentPublication": {
"id": "proceedings/fie/2012/1353/0",
"title": "2012 Frontiers in Education Conference Proceedings",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2017/5920/0/08190542",
"title": "Investigation of spatial visualization skills across world regions",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2017/08190542/12OmNy87QzI",
"parentPublication": {
"id": "proceedings/fie/2017/5920/0",
"title": "2017 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/latice/2015/9967/0/9967a164",
"title": "Delayed Guidance: A Teaching-Learning Strategy to Develop Ill-Structured Problem Solving Skills in Engineering",
"doi": null,
"abstractUrl": "/proceedings-article/latice/2015/9967a164/12OmNz5s0F4",
"parentPublication": {
"id": "proceedings/latice/2015/9967/0",
"title": "2015 International Conference on Learning and Teaching in Computing and Engineering (LaTiCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2014/4038/0/4038a401",
"title": "Improvement of Problem Solving Skills in Engineering Drawing Using Blender Based Mental Rotation Training",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2014/4038a401/12OmNzUPpdm",
"parentPublication": {
"id": "proceedings/icalt/2014/4038/0",
"title": "2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/t4e/2018/1143/0/114300a166",
"title": "Technology Enhanced Learning (TEL) Environment to Develop Expansionist-Reductionist (ER) Thinking Skills through Software Design Problem Solving",
"doi": null,
"abstractUrl": "/proceedings-article/t4e/2018/114300a166/17D45VTRosb",
"parentPublication": {
"id": "proceedings/t4e/2018/1143/0",
"title": "2018 IEEE Ninth International Conference on Technology for Education (T4E)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/re/2022/7000/0/700000a316",
"title": "Teaching and learning Requirements Engineering concepts: Peer-review skills vs. problem solving skills",
"doi": null,
"abstractUrl": "/proceedings-article/re/2022/700000a316/1HBKtVRBCO4",
"parentPublication": {
"id": "proceedings/re/2022/7000/0",
"title": "2022 IEEE 30th International Requirements Engineering Conference (RE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962750",
"title": "Improving engineering students’ problem-solving skills through think-aloud exercises",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962750/1IHnBWIc9RC",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1y4oEtZzwCQ",
"title": "2021 25th International Conference Information Visualisation (IV)",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1y4oJ9f6FuU",
"doi": "10.1109/IV53921.2021.00043",
"title": "A Taxonomy of Spatial-Temporal Data Visualization",
"normalizedTitle": "A Taxonomy of Spatial-Temporal Data Visualization",
"abstract": "Spatial-temporal data visualization is an important sub-field of data visualization. Many spatial-temporal data visualization techniques have been developed and published. Although there are several surveys on this subject, some are based on a task-centric or data-centric framework. Some surveys focus on the temporal data visualization for a particular type of spatial data visualization, such as a map or space-time cube. In this paper, we present a new taxonomy and interactive survey of spatial-temporal data visualization. Based on our taxonomy, a wide variety of spatial-temporal data visualization techniques can be described by a small set of visualization elements. This is the first step towards creating a grammar for spatial-temporal visualization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Spatial-temporal data visualization is an important sub-field of data visualization. Many spatial-temporal data visualization techniques have been developed and published. Although there are several surveys on this subject, some are based on a task-centric or data-centric framework. Some surveys focus on the temporal data visualization for a particular type of spatial data visualization, such as a map or space-time cube. In this paper, we present a new taxonomy and interactive survey of spatial-temporal data visualization. Based on our taxonomy, a wide variety of spatial-temporal data visualization techniques can be described by a small set of visualization elements. This is the first step towards creating a grammar for spatial-temporal visualization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Spatial-temporal data visualization is an important sub-field of data visualization. Many spatial-temporal data visualization techniques have been developed and published. Although there are several surveys on this subject, some are based on a task-centric or data-centric framework. Some surveys focus on the temporal data visualization for a particular type of spatial data visualization, such as a map or space-time cube. In this paper, we present a new taxonomy and interactive survey of spatial-temporal data visualization. Based on our taxonomy, a wide variety of spatial-temporal data visualization techniques can be described by a small set of visualization elements. This is the first step towards creating a grammar for spatial-temporal visualization.",
"fno": "382700a223",
"keywords": [
"Data Visualisation",
"Spatial Temporal Data Visualization",
"Data Centric Framework",
"Taxonomy",
"Space Time Cube",
"Map",
"Taxonomy",
"Data Visualization",
"Spatial Databases",
"Grammar",
"Task Analysis",
"Visualization",
"Spatial Temporal Analysis",
"Taxonomy"
],
"authors": [
{
"affiliation": "Creative Media Industries Institute, Georgia State University,Atlanta,USA",
"fullName": "Ying Zhu",
"givenName": "Ying",
"surname": "Zhu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Georgia State University,Department of Computer Science,Atlanta,USA",
"fullName": "Pragna Reddy Kancharla",
"givenName": "Pragna Reddy",
"surname": "Kancharla",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Georgia State University,Department of Computer Science,Atlanta,USA",
"fullName": "Chaitanya Sai Kumar Talluru",
"givenName": "Chaitanya Sai Kumar",
"surname": "Talluru",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-07-01T00:00:00",
"pubType": "proceedings",
"pages": "223-228",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-3827-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "382700a218",
"articleId": "1y4oIPnbyYU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "382700a229",
"articleId": "1y4oGJJ2HzW",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icde/2014/2555/0/06816766",
"title": "Managing uncertainty in spatial and spatio-temporal data",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2014/06816766/12OmNAQanxr",
"parentPublication": {
"id": "proceedings/icde/2014/2555/0",
"title": "2014 IEEE 30th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2017/2686/0/08109153",
"title": "TaRDIS, a Visual Analytics System for Spatial and Temporal Data in Archaeo-Related Disciplines",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2017/08109153/12OmNB0X8qi",
"parentPublication": {
"id": "proceedings/e-science/2017/2686/0",
"title": "2017 IEEE 13th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-infovis/2005/2790/0/01532149",
"title": "Temporal visualization of planning polygons for efficient partitioning of geo-spatial data",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/2005/01532149/12OmNyuy9Sb",
"parentPublication": {
"id": "proceedings/ieee-infovis/2005/2790/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccie/2010/4026/2/4026b153",
"title": "Application of Visualization Technology in Spatial Data Mining",
"doi": null,
"abstractUrl": "/proceedings-article/ccie/2010/4026b153/12OmNzBOhXD",
"parentPublication": {
"id": "proceedings/ccie/2010/4026/2",
"title": "Computing, Control and Industrial Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/infvis/2005/9464/0/01532149",
"title": "Temporal visualization of planning polygons for efficient partitioning of geo-spatial data",
"doi": null,
"abstractUrl": "/proceedings-article/infvis/2005/01532149/12OmNzaQoLh",
"parentPublication": {
"id": "proceedings/infvis/2005/9464/0",
"title": "IEEE Symposium on Information Visualization (InfoVis 05)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-infovis/2005/2790/0/27900028",
"title": "Temporal Visualization of Planning Polygons for Efficient Partitioning of Geo-Spatial Data",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/2005/27900028/12OmNzb7Znj",
"parentPublication": {
"id": "proceedings/ieee-infovis/2005/2790/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/03/ttg2014030365",
"title": "A Task Taxonomy for Network Evolution Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2014/03/ttg2014030365/13rRUxly95z",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2022/9744/0/974400a451",
"title": "Knowledge Discovery from Qualitative Spatial and Temporal Data",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2022/974400a451/1MrG2Bvp5ss",
"parentPublication": {
"id": "proceedings/ictai/2022/9744/0",
"title": "2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a236",
"title": "Integrated Spatio-temporal Storyline Visualization with Low Crossover",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a236/1rSR7y0mRfW",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a367",
"title": "A Classification of Augmented Reality Approaches for Spatial Data Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a367/1yeQHlFhK0w",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNCmpcNk",
"title": "Visualization Conference, IEEE",
"acronym": "ieee-vis",
"groupId": "1000796",
"volume": "0",
"displayVolume": "0",
"year": "2005",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzYNN5Q",
"doi": "10.1109/VISUAL.2005.1532792",
"title": "Query-driven visualization of large data sets",
"normalizedTitle": "Query-driven visualization of large data sets",
"abstract": "We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is constrained to the subset of data deemed interesting by the user. In many scientific data analysis applications, \"interesting\" data can be defined by compound Boolean range queries of the form (temperature>1000) AND (70<pressure<90). As data sizes grow larger, a central challenge is to answer such queries as efficiently as possible. Prior work in the visualization community has focused on answering range queries for scalar fields within the context of accelerating the search phase of isosurface algorithms. In contrast, our work describes an approach that leverages state-of-the-art indexing technology from the scientific data management community called \"bitmap indexing\". Our implementation, which we call \"DEX\" (short for dextrous data explorer), uses bitmap indexing to efficiently answer multivariate, multidimensional data queries to provide input to a visualization pipeline. We present an analysis overview and benchmark results that show bitmap indexing offers significant storage and performance improvements when compared to previous approaches for accelerating the search phase of isosurface algorithms. More importantly, since bitmap indexing supports complex multidimensional, multivariate range queries, it is more generally applicable to scientific data visualization and analysis problems. In addition to benchmark performance and analysis, we apply DEX to a typical scientific visualization problem encountered in combustion simulation data analysis.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is constrained to the subset of data deemed interesting by the user. In many scientific data analysis applications, \"interesting\" data can be defined by compound Boolean range queries of the form (temperature>1000) AND (70<pressure<90). As data sizes grow larger, a central challenge is to answer such queries as efficiently as possible. Prior work in the visualization community has focused on answering range queries for scalar fields within the context of accelerating the search phase of isosurface algorithms. In contrast, our work describes an approach that leverages state-of-the-art indexing technology from the scientific data management community called \"bitmap indexing\". Our implementation, which we call \"DEX\" (short for dextrous data explorer), uses bitmap indexing to efficiently answer multivariate, multidimensional data queries to provide input to a visualization pipeline. We present an analysis overview and benchmark results that show bitmap indexing offers significant storage and performance improvements when compared to previous approaches for accelerating the search phase of isosurface algorithms. More importantly, since bitmap indexing supports complex multidimensional, multivariate range queries, it is more generally applicable to scientific data visualization and analysis problems. In addition to benchmark performance and analysis, we apply DEX to a typical scientific visualization problem encountered in combustion simulation data analysis.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is constrained to the subset of data deemed interesting by the user. In many scientific data analysis applications, \"interesting\" data can be defined by compound Boolean range queries of the form (temperature>1000) AND (70<pressure<90). As data sizes grow larger, a central challenge is to answer such queries as efficiently as possible. Prior work in the visualization community has focused on answering range queries for scalar fields within the context of accelerating the search phase of isosurface algorithms. In contrast, our work describes an approach that leverages state-of-the-art indexing technology from the scientific data management community called \"bitmap indexing\". Our implementation, which we call \"DEX\" (short for dextrous data explorer), uses bitmap indexing to efficiently answer multivariate, multidimensional data queries to provide input to a visualization pipeline. We present an analysis overview and benchmark results that show bitmap indexing offers significant storage and performance improvements when compared to previous approaches for accelerating the search phase of isosurface algorithms. More importantly, since bitmap indexing supports complex multidimensional, multivariate range queries, it is more generally applicable to scientific data visualization and analysis problems. In addition to benchmark performance and analysis, we apply DEX to a typical scientific visualization problem encountered in combustion simulation data analysis.",
"fno": "01532792",
"keywords": [
"Data Visualisation",
"Rendering Computer Graphics",
"Query Processing",
"Very Large Databases",
"Database Indexing",
"Query Driven Visualization",
"Large Data Sets",
"Scientific Data Management",
"Bitmap Indexing",
"Dextrous Data Explorer",
"Multidimensional Data Queries",
"Visualization Pipeline",
"Isosurface Algorithms",
"Combustion Simulation Data Analysis",
"Data Visualization",
"Indexing",
"Data Analysis",
"Acceleration",
"Isosurfaces",
"Multidimensional Systems",
"Performance Analysis",
"Humans",
"Temperature Distribution",
"Technology Management"
],
"authors": [
{
"affiliation": "Computational Res. Div., Lawrence Berkeley Lab., CA, USA",
"fullName": "K. Stockinger",
"givenName": "K.",
"surname": "Stockinger",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computational Res. Div., Lawrence Berkeley Lab., CA, USA",
"fullName": "J. Shalf",
"givenName": "J.",
"surname": "Shalf",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computational Res. Div., Lawrence Berkeley Lab., CA, USA",
"fullName": "K. Wu",
"givenName": "K.",
"surname": "Wu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computational Res. Div., Lawrence Berkeley Lab., CA, USA",
"fullName": "E.W. Bethel",
"givenName": "E.W.",
"surname": "Bethel",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ieee-vis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2005-01-01T00:00:00",
"pubType": "proceedings",
"pages": "167,168,169,170,171,172,173,174",
"year": "2005",
"issn": null,
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "27660006",
"articleId": "12OmNAle6M8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "27660007",
"articleId": "12OmNCmpcT8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ipdpsw/2012/4676/0/4676c104",
"title": "The Chunk-Locality Index: An Efficient Query Method for Climate Datasets",
"doi": null,
"abstractUrl": "/proceedings-article/ipdpsw/2012/4676c104/12OmNAfPIRb",
"parentPublication": {
"id": "proceedings/ipdpsw/2012/4676/0",
"title": "2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2013/4909/0/06544836",
"title": "An efficient and compact indexing scheme for large-scale data store",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2013/06544836/12OmNrFkeSz",
"parentPublication": {
"id": "proceedings/icde/2013/4909/0",
"title": "2013 29th IEEE International Conference on Data Engineering (ICDE 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ic2e/2015/8218/0/8218a508",
"title": "Compressed Hierarchical Bitmaps for Efficiently Processing Different Query Workloads",
"doi": null,
"abstractUrl": "/proceedings-article/ic2e/2015/8218a508/12OmNrY3Lxt",
"parentPublication": {
"id": "proceedings/ic2e/2015/8218/0",
"title": "2015 IEEE International Conference on Cloud Engineering (IC2E)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/27660022",
"title": "Query-Driven Visualization of Large Data Sets",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/27660022/12OmNvAAtDg",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icinis/2013/2809/0/2809a316",
"title": "A Survey on Bitmap Index Technologies for Large-Scale Data Retrieval",
"doi": null,
"abstractUrl": "/proceedings-article/icinis/2013/2809a316/12OmNwEJ0CU",
"parentPublication": {
"id": "proceedings/icinis/2013/2809/0",
"title": "2013 6th International Conference on Intelligent Networks and Intelligent Systems (ICINIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipdps/2006/0054/0/01639304",
"title": "Bitmap indexes for large scientific data sets: a case study",
"doi": null,
"abstractUrl": "/proceedings-article/ipdps/2006/01639304/12OmNwp74Nh",
"parentPublication": {
"id": "proceedings/ipdps/2006/0054/0",
"title": "Proceedings 20th IEEE International Parallel & Distributed Processing Symposium",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/nss/2010/4159/0/4159a477",
"title": "Spatio-temporal Knowledge Discovery in Very Large METOC Data Sets",
"doi": null,
"abstractUrl": "/proceedings-article/nss/2010/4159a477/12OmNyuy9TY",
"parentPublication": {
"id": "proceedings/nss/2010/4159/0",
"title": "Network and System Security, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2006/0591/0/04035755",
"title": "Accelerating Network Traffic Analytics Using Query-Driven Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2006/04035755/12OmNzn38Ji",
"parentPublication": {
"id": "proceedings/vast/2006/0591/0",
"title": "2006 IEEE Symposium On Visual Analytics Science And Technology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2006/2700/0/04090213",
"title": "Detecting Distributed Scans Using High-Performance Query-Driven Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2006/04090213/17D45VUZMVV",
"parentPublication": {
"id": "proceedings/sc/2006/2700/0",
"title": "SC Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09005666",
"title": "Multidimensional Preference Query Optimization on Infrastructure Monitoring Systems",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09005666/1hJrPXvoEdG",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1A8gmCnipkA",
"title": "2021 IEEE International Conference on Big Data (Big Data)",
"acronym": "big-data",
"groupId": "1802964",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1A8hk7jo2oo",
"doi": "10.1109/BigData52589.2021.9671942",
"title": "Scientific Formula Retrieval via Tree Embeddings",
"normalizedTitle": "Scientific Formula Retrieval via Tree Embeddings",
"abstract": "Exploiting the ever-growing corpus of scientific content calls for new ways and means to effectively organize, search, and retrieve scientific formulae. We propose a new data-driven framework for retrieving similar scientific formulae via learned formula representations based on tree embeddings. FORTE (for FOrmula Representation learning via Tree Embeddings) leverages operator tree representations of symbolic scientific formulae (such as math equations) to explicitly capture their inherent structural and semantic properties. FORTE employs i) a tree encoder that encodes the formula’s operator tree into an embedding vector and ii) a tree decoder that directly generates a formula’s operator tree from the embedding vector. We also develop a novel tree beam search algorithm that improves the quality of the decoded operator trees. We demonstrate that FORTE (sometimes significantly) outperforms various baseline methods on formula reconstruction and retrieval using a real-world dataset comprising 770k scientific formulae collected on-line.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Exploiting the ever-growing corpus of scientific content calls for new ways and means to effectively organize, search, and retrieve scientific formulae. We propose a new data-driven framework for retrieving similar scientific formulae via learned formula representations based on tree embeddings. FORTE (for FOrmula Representation learning via Tree Embeddings) leverages operator tree representations of symbolic scientific formulae (such as math equations) to explicitly capture their inherent structural and semantic properties. FORTE employs i) a tree encoder that encodes the formula’s operator tree into an embedding vector and ii) a tree decoder that directly generates a formula’s operator tree from the embedding vector. We also develop a novel tree beam search algorithm that improves the quality of the decoded operator trees. We demonstrate that FORTE (sometimes significantly) outperforms various baseline methods on formula reconstruction and retrieval using a real-world dataset comprising 770k scientific formulae collected on-line.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Exploiting the ever-growing corpus of scientific content calls for new ways and means to effectively organize, search, and retrieve scientific formulae. We propose a new data-driven framework for retrieving similar scientific formulae via learned formula representations based on tree embeddings. FORTE (for FOrmula Representation learning via Tree Embeddings) leverages operator tree representations of symbolic scientific formulae (such as math equations) to explicitly capture their inherent structural and semantic properties. FORTE employs i) a tree encoder that encodes the formula’s operator tree into an embedding vector and ii) a tree decoder that directly generates a formula’s operator tree from the embedding vector. We also develop a novel tree beam search algorithm that improves the quality of the decoded operator trees. We demonstrate that FORTE (sometimes significantly) outperforms various baseline methods on formula reconstruction and retrieval using a real-world dataset comprising 770k scientific formulae collected on-line.",
"fno": "09671942",
"keywords": [
"Data Mining",
"Information Retrieval",
"Mathematics Computing",
"Search Problems",
"Symbol Manipulation",
"Trees Mathematics",
"Scientific Formula Retrieval",
"Tree Embeddings",
"Scientific Content",
"FORTE",
"Formula Representation",
"Operator Tree Representations",
"Symbolic Scientific Formulae",
"Tree Encoder",
"Embedding Vector",
"Tree Decoder",
"Tree Beam Search Algorithm",
"Formula Reconstruction",
"Representation Learning",
"Conferences",
"Semantics",
"Big Data",
"Mathematical Models",
"Data Models",
"Decoding",
"Representation Learning",
"Scientific Formulae Understanding",
"Information Retrieval",
"Generative Models",
"Tree Structured Data"
],
"authors": [
{
"affiliation": "Rice University,Dept. Electrical and Computer Engineering,Houston,TX,USA",
"fullName": "Zichao Wang",
"givenName": "Zichao",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Massachusetts, Amherst,College of Information and Computer Sciences,Amherst,MA,USA",
"fullName": "Mengxue Zhang",
"givenName": "Mengxue",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rice University,Dept. Electrical and Computer Engineering,Houston,TX,USA",
"fullName": "Richard G. Baraniuk",
"givenName": "Richard G.",
"surname": "Baraniuk",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Massachusetts, Amherst,College of Information and Computer Sciences,Amherst,MA,USA",
"fullName": "Andrew S. Lan",
"givenName": "Andrew S.",
"surname": "Lan",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "big-data",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-12-01T00:00:00",
"pubType": "proceedings",
"pages": "1493-1503",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-3902-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09671918",
"articleId": "1A8gDx5sRcQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09671581",
"articleId": "1A8jeeXkENO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2017/3586/1/3586b144",
"title": "A Symbol Dominance Based Formulae Recognition Approach for PDF Documents",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2017/3586b144/12OmNAHEpA3",
"parentPublication": {
"id": "proceedings/icdar/2017/3586/1",
"title": "2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2017/3586/1/3586a553",
"title": "A Deep Learning-Based Formula Detection Method for PDF Documents",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2017/3586a553/12OmNAo45R6",
"parentPublication": {
"id": "proceedings/icdar/2017/3586/1",
"title": "2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/time/2011/1242/0/06065228",
"title": "An Experimental Comparison of Theorem Provers for CTL",
"doi": null,
"abstractUrl": "/proceedings-article/time/2011/06065228/12OmNBQTJe0",
"parentPublication": {
"id": "proceedings/time/2011/1242/0",
"title": "2011 Eighteenth International Symposium on Temporal Representation and Reasoning (TIME 2011)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2016/4229/0/07559613",
"title": "A mathematical information retrieval system based on RankBoost",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2016/07559613/12OmNro0IgD",
"parentPublication": {
"id": "proceedings/jcdl/2016/4229/0",
"title": "2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvisp/2017/0612/0/0612a114",
"title": "An Improved Formula Extraction Method of Printed Chinese Layouts Based on Connected Component Run-Length Feature",
"doi": null,
"abstractUrl": "/proceedings-article/icvisp/2017/0612a114/12OmNwCsdCY",
"parentPublication": {
"id": "proceedings/icvisp/2017/0612/0",
"title": "2017 International Conference on Vision, Image and Signal Processing (ICVISP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2001/1263/0/12630762",
"title": "Mathematical Formula Recognition Using Virtual Link Network",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2001/12630762/12OmNxzuMNl",
"parentPublication": {
"id": "proceedings/icdar/2001/1263/0",
"title": "Proceedings of Sixth International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ase/2000/0710/0/00873678",
"title": "An experiment in scientific program understanding",
"doi": null,
"abstractUrl": "/proceedings-article/ase/2000/00873678/12OmNyKJion",
"parentPublication": {
"id": "proceedings/ase/2000/0710/0",
"title": "Proceedings ASE 2000. Fifteenth IEEE International Conference on Automated Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/5555/01/09896871",
"title": "<inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathtt {Radar}$_Z</tex-math></inline-formula>: Adversarial Driving Style Representation Learning With Data Augmentation",
"doi": null,
"abstractUrl": "/journal/tm/5555/01/09896871/1GQIE9McVri",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09944955",
"title": "<inline-formula><tex-math notation=\"LaTeX\">Z_$kt$_Z</tex-math></inline-formula>-Safety: Graph Release via <inline-formula><tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math></inline-formula>-Anonymity and <inline-formula><tex-math notation=\"LaTeX\">Z_$t$_Z</tex-math></inline-formula>-Closeness",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09944955/1IbM9dSufYI",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2023/01/09380370",
"title": "High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data",
"doi": null,
"abstractUrl": "/journal/bd/2023/01/09380370/1s2FYtnQsZq",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KxUhhFgzlK",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2023",
"__typename": "ProceedingType"
},
"article": {
"id": "1KxVNTDTu80",
"doi": "10.1109/WACV56688.2023.00530",
"title": "Learning Latent Structural Relations with Message Passing Prior",
"normalizedTitle": "Learning Latent Structural Relations with Message Passing Prior",
"abstract": "Learning disentangled representations is an important topic in machine learning with a wide range of applications. Disentangled latent variables represent interpretable semantic information and reflect separate factors of variation in data. Although generative models can learn latent representations as well, most existing models ignore the structural information among latent variables. In this paper, we propose a novel approach to learn the disentangled latent structural representations from data using decomposable variational auto-encoders. We design a novel message passing prior for the latent representations to capture the interactions among different data components. Different from many previous methods that ignore data component or object interaction, our approach simultaneously learns component representation and encodes component relationships. We have applied our model to tasks of data segmentation and latent representation learning among different data components. Experiments on several benchmarks demonstrate the utility of the proposed method.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Learning disentangled representations is an important topic in machine learning with a wide range of applications. Disentangled latent variables represent interpretable semantic information and reflect separate factors of variation in data. Although generative models can learn latent representations as well, most existing models ignore the structural information among latent variables. In this paper, we propose a novel approach to learn the disentangled latent structural representations from data using decomposable variational auto-encoders. We design a novel message passing prior for the latent representations to capture the interactions among different data components. Different from many previous methods that ignore data component or object interaction, our approach simultaneously learns component representation and encodes component relationships. We have applied our model to tasks of data segmentation and latent representation learning among different data components. Experiments on several benchmarks demonstrate the utility of the proposed method.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Learning disentangled representations is an important topic in machine learning with a wide range of applications. Disentangled latent variables represent interpretable semantic information and reflect separate factors of variation in data. Although generative models can learn latent representations as well, most existing models ignore the structural information among latent variables. In this paper, we propose a novel approach to learn the disentangled latent structural representations from data using decomposable variational auto-encoders. We design a novel message passing prior for the latent representations to capture the interactions among different data components. Different from many previous methods that ignore data component or object interaction, our approach simultaneously learns component representation and encodes component relationships. We have applied our model to tasks of data segmentation and latent representation learning among different data components. Experiments on several benchmarks demonstrate the utility of the proposed method.",
"fno": "934600f323",
"keywords": [
"Learning Artificial Intelligence",
"Message Passing",
"Neural Nets",
"Data Segmentation",
"Decomposable Variational Auto Encoders",
"Disentangled Latent Structural Representations",
"Disentangled Latent Variables",
"Latent Representation Learning",
"Latent Structural Relations",
"Machine Learning",
"Message Passing",
"Representation Learning",
"Computer Vision",
"Message Passing",
"Semantics",
"Benchmark Testing",
"Data Models",
"Task Analysis",
"Algorithms Machine Learning Architectures",
"Formulations",
"And Algorithms Including Transfer",
"Image Recognition And Understanding Object Detection",
"Categorization",
"Segmentation",
"Scene Modeling",
"Visual Reasoning"
],
"authors": [
{
"affiliation": "Cognitive Computing Lab,Baidu Research,Bellevue,WA,USA,98004",
"fullName": "Shaogang Ren",
"givenName": "Shaogang",
"surname": "Ren",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cognitive Computing Lab,Baidu Research,Bellevue,WA,USA,98004",
"fullName": "Hongliang Fei",
"givenName": "Hongliang",
"surname": "Fei",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cognitive Computing Lab,Baidu Research,Bellevue,WA,USA,98004",
"fullName": "Dingcheng Li",
"givenName": "Dingcheng",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cognitive Computing Lab,Baidu Research,Bellevue,WA,USA,98004",
"fullName": "Ping Li",
"givenName": "Ping",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2023-01-01T00:00:00",
"pubType": "proceedings",
"pages": "5323-5332",
"year": "2023",
"issn": null,
"isbn": "978-1-6654-9346-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1KxVNQ0NzYQ",
"name": "pwacv202393460-010030305s1-mm_934600f323.zip",
"size": "2.79 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pwacv202393460-010030305s1-mm_934600f323.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "934600f313",
"articleId": "1KxVvIlXAOs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "934600f333",
"articleId": "1KxVrBfGr9C",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2021/0126/0/09669692",
"title": "Deep Latent-Variable Models for Controllable Molecule Generation",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669692/1A9Vddc6bFS",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200d672",
"title": "Disentangled Representation for Age-Invariant Face Recognition: A Mutual Information Minimization Perspective",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200d672/1BmGoyrVepi",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09893319",
"title": "Disentangled Graph Contrastive Learning With Independence Promotion",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09893319/1GGLdk7AjO8",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2022/8045/0/10021114",
"title": "SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2022/10021114/1KfR4QqVlbG",
"parentPublication": {
"id": "proceedings/big-data/2022/8045/0",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2022/5099/0/509900a648",
"title": "Detach and Enhance: Learning Disentangled Cross-modal Latent Representation for Efficient Face-Voice Association and Matching",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2022/509900a648/1KpCkDzDOBG",
"parentPublication": {
"id": "proceedings/icdm/2022/5099/0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2023/9346/0/934600b531",
"title": "Representation Disentanglement in Generative Models with Contrastive Learning",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600b531/1L8qx7egobS",
"parentPublication": {
"id": "proceedings/wacv/2023/9346/0",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700a645",
"title": "Representation Learning Through Latent Canonicalizations",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700a645/1uqGyIaXUuk",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2021/4899/0/489900b257",
"title": "On Disentanglement and Mutual Information in Semi-Supervised Variational Auto-Encoders",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2021/489900b257/1yJYw69RUcg",
"parentPublication": {
"id": "proceedings/cvprw/2021/4899/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100b081",
"title": "Relational Prior for Multi-Object Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100b081/1yNhuto1wI0",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2021/4899/0/489900b692",
"title": "Private-Shared Disentangled Multimodal VAE for Learning of Latent Representations",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2021/489900b692/1yZ4y9uUPfi",
"parentPublication": {
"id": "proceedings/cvprw/2021/4899/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBSBk6v",
"title": "Dagstuhl '97 - Scientific Visualization Conference",
"acronym": "dagstuhl",
"groupId": "1811924",
"volume": "0",
"displayVolume": "0",
"year": "1997",
"__typename": "ProceedingType"
},
"article": {
"id": "1h0N3jxcLQs",
"doi": "10.1109/DAGSTUHL.1997.1423097",
"title": "An Introduction to Wavelets for Scientific Visualization",
"normalizedTitle": "An Introduction to Wavelets for Scientific Visualization",
"abstract": "This paper gives an introduction to wavelet techniques in the context of Scientific Visualization. Wavelets are a powerful tool for the representation of large and complex data sets. Some restrictions apply on the type of data sets which can be represented by wavelets. These restrictions are described in a first part. Thereafter, the basic concepts of wavelet representations are explained: level of detail spaces, wavelet spaces, decomposition and reconstruction algorithms. Orthogonality properties of wavelets and their relations with the ability of computing best approximations are the subject of the next part. Usual applications of wavelet representations in Scientific Visualization are then reviewed. These include progressive transmission, LOD visualization, local area zooming. The last part is dedicated to a recent generalization of wavelet techniques that deals with some types of data sets that cannot be tackle by usual wavelet representations due to the restrictions described in the first part.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper gives an introduction to wavelet techniques in the context of Scientific Visualization. Wavelets are a powerful tool for the representation of large and complex data sets. Some restrictions apply on the type of data sets which can be represented by wavelets. These restrictions are described in a first part. Thereafter, the basic concepts of wavelet representations are explained: level of detail spaces, wavelet spaces, decomposition and reconstruction algorithms. Orthogonality properties of wavelets and their relations with the ability of computing best approximations are the subject of the next part. Usual applications of wavelet representations in Scientific Visualization are then reviewed. These include progressive transmission, LOD visualization, local area zooming. The last part is dedicated to a recent generalization of wavelet techniques that deals with some types of data sets that cannot be tackle by usual wavelet representations due to the restrictions described in the first part.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper gives an introduction to wavelet techniques in the context of Scientific Visualization. Wavelets are a powerful tool for the representation of large and complex data sets. Some restrictions apply on the type of data sets which can be represented by wavelets. These restrictions are described in a first part. Thereafter, the basic concepts of wavelet representations are explained: level of detail spaces, wavelet spaces, decomposition and reconstruction algorithms. Orthogonality properties of wavelets and their relations with the ability of computing best approximations are the subject of the next part. Usual applications of wavelet representations in Scientific Visualization are then reviewed. These include progressive transmission, LOD visualization, local area zooming. The last part is dedicated to a recent generalization of wavelet techniques that deals with some types of data sets that cannot be tackle by usual wavelet representations due to the restrictions described in the first part.",
"fno": "01423097",
"keywords": [
"Visualization",
"Multiresolution",
"Wavelets",
"Orthogonality",
"Data Visualization",
"Wavelet Transforms",
"Tail",
"Electrical Capacitance Tomography",
"Computer Graphics",
"Books",
"Bibliographies",
"Tensile Stress",
"Visualization",
"Multiresolution",
"Wavelets",
"Orthogonality"
],
"authors": [
{
"affiliation": "LMC",
"fullName": "G. Bonneau",
"givenName": "G.",
"surname": "Bonneau",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dagstuhl",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1997-01-01T00:00:00",
"pubType": "proceedings",
"pages": "16-16",
"year": "1997",
"issn": null,
"isbn": "0-7695-0503-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "01423096",
"articleId": "1h0N3f3SFLq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "01423098",
"articleId": "12OmNyU63u1",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icmtma/2009/3583/3/3583c313",
"title": "Study of Signal Feature Recognition Method Based on Morlet Combined Wavelets",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2009/3583c313/12OmNAYoKoE",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icig/2007/2929/0/29290081",
"title": "An Improved Method of Wavelets Basis Image Denoising Using Besov Norm Regularization",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2007/29290081/12OmNB06l8Z",
"parentPublication": {
"id": "proceedings/icig/2007/2929/0",
"title": "Image and Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2010/7491/0/05583171",
"title": "An efficient depth map estimation technique using complex wavelets",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2010/05583171/12OmNBEpnDG",
"parentPublication": {
"id": "proceedings/icme/2010/7491/0",
"title": "2010 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2008/1967/0/04493633",
"title": "Wavelets: An efficient tool for lung sounds analysis",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2008/04493633/12OmNqBKU3V",
"parentPublication": {
"id": "proceedings/aiccsa/2008/1967/0",
"title": "2008 IEEE/ACS International Conference on Computer Systems and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icassp/1992/0532/4/00226356",
"title": "Multiresolution representations using the auto-correlation functions of compactly supported wavelets",
"doi": null,
"abstractUrl": "/proceedings-article/icassp/1992/00226356/12OmNxA3Z45",
"parentPublication": {
"id": "proceedings/icassp/1992/0532/4",
"title": "Acoustics, Speech, and Signal Processing, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dagstuhl/1997/0503/0/05030016",
"title": "An Introduction to Wavelets for Scientific Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/dagstuhl/1997/05030016/12OmNzcPA6s",
"parentPublication": {
"id": "proceedings/dagstuhl/1997/0503/0",
"title": "Dagstuhl '97 - Scientific Visualization Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/1995/02/c2050",
"title": "An Introduction to Wavelets",
"doi": null,
"abstractUrl": "/magazine/cs/1995/02/c2050/13rRUwjoNAD",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192734",
"title": "Adaptive Multilinear Tensor Product Wavelets",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192734/13rRUxcsYLR",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1996/10/i0959",
"title": "Image Representation Using 2D Gabor Wavelets",
"doi": null,
"abstractUrl": "/journal/tp/1996/10/i0959/13rRUxjQywl",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dagstuhl/1997/0503/0/01423124",
"title": "Scientific Visualization on Sparse Grids",
"doi": null,
"abstractUrl": "/proceedings-article/dagstuhl/1997/01423124/1h0N4grxsuA",
"parentPublication": {
"id": "proceedings/dagstuhl/1997/0503/0",
"title": "Dagstuhl '97 - Scientific Visualization Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1pZ0TbXJiBq",
"title": "2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV)",
"acronym": "ldav",
"groupId": "1800568",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1pZ0TITco5q",
"doi": "10.1109/LDAV51489.2020.00010",
"title": "Interactive Visualization of Terascale Data in the Browser: Fact or Fiction?",
"normalizedTitle": "Interactive Visualization of Terascale Data in the Browser: Fact or Fiction?",
"abstract": "Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser.",
"fno": "846800a027",
"keywords": [
"Data Compression",
"Data Visualisation",
"Interactive Systems",
"Online Front Ends",
"Parallel Processing",
"Block Compressed Data Sets",
"Interactive Isosurface Computation",
"Web Browser",
"Scientific Visualization Tasks",
"Interactive Visualization",
"Terascale Data",
"Information Visualization",
"Scientific Visualization",
"Native Code Libraries",
"Large Scale Scientific Data",
"Resource Constrained Environment",
"Web Assembly",
"Web GPU",
"Parallel Processing",
"Browsers",
"Isosurfaces",
"Graphics Processing Units",
"Servers",
"Rendering Computer Graphics",
"Libraries",
"Arrays",
"Web Applications",
"Parallel Isosurface Extraction"
],
"authors": [
{
"affiliation": "University of Utah,SCI Institute",
"fullName": "Will Usher",
"givenName": "Will",
"surname": "Usher",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Utah,SCI Institute",
"fullName": "Valerio Pascucci",
"givenName": "Valerio",
"surname": "Pascucci",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ldav",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-10-01T00:00:00",
"pubType": "proceedings",
"pages": "27-36",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-8468-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "846800a022",
"articleId": "1pZ0Tm5TBsc",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "846800a037",
"articleId": "1pZ0U4aglxe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sp/2011/4402/0/4402a115",
"title": "Verified Security for Browser Extensions",
"doi": null,
"abstractUrl": "/proceedings-article/sp/2011/4402a115/12OmNvnOwyb",
"parentPublication": {
"id": "proceedings/sp/2011/4402/0",
"title": "2011 IEEE Symposium on Security and Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acit-csi/2015/9642/0/9642a103",
"title": "Static Analysis Technique of Cross-Browser Compatibility Detecting",
"doi": null,
"abstractUrl": "/proceedings-article/acit-csi/2015/9642a103/12OmNxQOjEr",
"parentPublication": {
"id": "proceedings/acit-csi/2015/9642/0",
"title": "2015 3rd International Conference on Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligence (ACIT-CSI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sp/2018/4353/0/435301a054",
"title": "FP-STALKER: Tracking Browser Fingerprint Evolutions Along Time",
"doi": null,
"abstractUrl": "/proceedings-article/sp/2018/435301a054/12OmNyGtjcF",
"parentPublication": {
"id": "proceedings/sp/2018/4353/0",
"title": "2018 IEEE Symposium on Security and Privacy (SP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2017/5738/0/08031592",
"title": "Efficient GPU-accelerated computation of isosurface similarity maps",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2017/08031592/12OmNyNzhyo",
"parentPublication": {
"id": "proceedings/pacificvis/2017/5738/0",
"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/searis/2013/3136/0/06798107",
"title": "ARML 2.0 in the context of existing AR data formats",
"doi": null,
"abstractUrl": "/proceedings-article/searis/2013/06798107/12OmNyvoXgD",
"parentPublication": {
"id": "proceedings/searis/2013/3136/0",
"title": "2013 6th Workshop on Software Engineering and Architectures for Realtime Interactive Systems (SEARIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2014/6854/0/6854a110",
"title": "Research of Collaborative Interactive Visualization for Medical Imaging",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2014/6854a110/12OmNzzP5Ql",
"parentPublication": {
"id": "proceedings/icvrv/2014/6854/0",
"title": "2014 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2006/05/v1267",
"title": "Interactive Point-based Isosurface Exploration and High-quality Rendering",
"doi": null,
"abstractUrl": "/journal/tg/2006/05/v1267/13rRUxjQyhm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2014/01/mcs2014010024",
"title": "Importance-Driven Isosurface Decimation for Visualization of Large Simulation Data Based on OpenCL",
"doi": null,
"abstractUrl": "/magazine/cs/2014/01/mcs2014010024/13rRUxjyWZx",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2015/04/07182778",
"title": "Volume Haptics with Topology-Consistent Isosurfaces",
"doi": null,
"abstractUrl": "/journal/th/2015/04/07182778/13rRUypp57K",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904483",
"title": "IDLat: An Importance-Driven Latent Generation Method for Scientific Data",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904483/1H1gfbVcpgI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JNqMydZTHi",
"title": "2022 International Conference on Advanced Computing and Analytics (ACOMPA)",
"acronym": "acompa",
"groupId": "1848652",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JNqOqDO1bO",
"doi": "10.1109/ACOMPA57018.2022.00010",
"title": "Toward Code Generation for Process-oriented, Role-based Dashboards : An Example of Digital Advertising in Vietnam",
"normalizedTitle": "Toward Code Generation for Process-oriented, Role-based Dashboards : An Example of Digital Advertising in Vietnam",
"abstract": "With the rise of data visualization techniques, dashboard engineering has attracted a great deal of attention in the last decade, but has been hampered by a lack of automation tools. In today’s enterprise systems, business users expect dashboards to be more process-oriented in addition to being context-sensitive. While many commercial business intelligence tools offer role-based dashboard, the idea of constructing a process-oriented dashboard has drawn the attention of scholars in recent years. The paper reports on our preliminary work in the generation of such a dashboard by iterating through all the pools and data objects visually depicted in a business process and generating the computer-interpretable source code that represents the corresponding visualization charts. To make this process-oriented dashboard lively visible, we load a real dataset together with the generated source code into a dashboard-rendering library. To demonstrate the relevance of our work, we walk through a real-life digital advertising project and illustrate how a dashboard could be generated and rendered for a given business process.",
"abstracts": [
{
"abstractType": "Regular",
"content": "With the rise of data visualization techniques, dashboard engineering has attracted a great deal of attention in the last decade, but has been hampered by a lack of automation tools. In today’s enterprise systems, business users expect dashboards to be more process-oriented in addition to being context-sensitive. While many commercial business intelligence tools offer role-based dashboard, the idea of constructing a process-oriented dashboard has drawn the attention of scholars in recent years. The paper reports on our preliminary work in the generation of such a dashboard by iterating through all the pools and data objects visually depicted in a business process and generating the computer-interpretable source code that represents the corresponding visualization charts. To make this process-oriented dashboard lively visible, we load a real dataset together with the generated source code into a dashboard-rendering library. To demonstrate the relevance of our work, we walk through a real-life digital advertising project and illustrate how a dashboard could be generated and rendered for a given business process.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "With the rise of data visualization techniques, dashboard engineering has attracted a great deal of attention in the last decade, but has been hampered by a lack of automation tools. In today’s enterprise systems, business users expect dashboards to be more process-oriented in addition to being context-sensitive. While many commercial business intelligence tools offer role-based dashboard, the idea of constructing a process-oriented dashboard has drawn the attention of scholars in recent years. The paper reports on our preliminary work in the generation of such a dashboard by iterating through all the pools and data objects visually depicted in a business process and generating the computer-interpretable source code that represents the corresponding visualization charts. To make this process-oriented dashboard lively visible, we load a real dataset together with the generated source code into a dashboard-rendering library. To demonstrate the relevance of our work, we walk through a real-life digital advertising project and illustrate how a dashboard could be generated and rendered for a given business process.",
"fno": "617100a020",
"keywords": [
"Advertising",
"Business Data Processing",
"Competitive Intelligence",
"Data Visualisation",
"Program Compilers",
"Business Process",
"Code Generation",
"Commercial Business Intelligence Tools",
"Computer Interpretable Source Code",
"Dashboard Rendering Library",
"Data Visualization Techniques",
"Digital Advertising Project",
"Process Oriented Dashboard",
"Role Based Dashboard",
"Vietnam",
"Visualization Charts",
"Codes",
"Automation",
"Source Coding",
"Data Visualization",
"Libraries",
"Business Process Management",
"Business Intelligence",
"Dashboard",
"Business Process Management",
"Business Intelligence"
],
"authors": [
{
"affiliation": "Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM),Faculty of Computer Science & Engineering,Ho Chi Minh City,Vietnam",
"fullName": "Nga Nguyen",
"givenName": "Nga",
"surname": "Nguyen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM),Faculty of Computer Science & Engineering,Ho Chi Minh City,Vietnam",
"fullName": "Lam-Son Lê",
"givenName": "Lam-Son",
"surname": "Lê",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "acompa",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-11-01T00:00:00",
"pubType": "proceedings",
"pages": "20-26",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6171-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "617100a012",
"articleId": "1JNqOFTT3IQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "617100a027",
"articleId": "1JNqMGpOhoI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/securware/2009/3668/0/3668a136",
"title": "Extending Role-Based Access Control for Business Usage",
"doi": null,
"abstractUrl": "/proceedings-article/securware/2009/3668a136/12OmNAoUTm8",
"parentPublication": {
"id": "proceedings/securware/2009/3668/0",
"title": "2009 Third International Conference on Emerging Security Information, Systems and Technologies",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/edoc/2006/2558/0/25580374",
"title": "Model-Driven Dashboards for Business Performance Reporting",
"doi": null,
"abstractUrl": "/proceedings-article/edoc/2006/25580374/12OmNBPc8tG",
"parentPublication": {
"id": "proceedings/edoc/2006/2558/0",
"title": "2006 10th IEEE International Enterprise Distributed Object Computing Conference (EDOC'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi-iat/2010/4191/3/4191c045",
"title": "The Inter-organizational Business Collaboration Oriented Role Model for E-government",
"doi": null,
"abstractUrl": "/proceedings-article/wi-iat/2010/4191c045/12OmNqFJhSp",
"parentPublication": {
"id": "proceedings/wi-iat/2010/4191/2",
"title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsiit/2017/9899/0/9899a331",
"title": "Executive Dashboard as a Tool for Knowledge Discovery",
"doi": null,
"abstractUrl": "/proceedings-article/icsiit/2017/9899a331/12OmNsdo6wu",
"parentPublication": {
"id": "proceedings/icsiit/2017/9899/0",
"title": "2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vissoft/2022/8092/0/809200a172",
"title": "VizAPI: Visualizing Interactions between Java Libraries and Clients",
"doi": null,
"abstractUrl": "/proceedings-article/vissoft/2022/809200a172/1JeEAFTTJ72",
"parentPublication": {
"id": "proceedings/vissoft/2022/8092/0",
"title": "2022 Working Conference on Software Visualization (VISSOFT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsme/2022/7956/0/795600a464",
"title": "COBREX: A Tool for Extracting Business Rules from COBOL",
"doi": null,
"abstractUrl": "/proceedings-article/icsme/2022/795600a464/1JeFivgJU1G",
"parentPublication": {
"id": "proceedings/icsme/2022/7956/0",
"title": "2022 IEEE International Conference on Software Maintenance and Evolution (ICSME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/snpd-winter/2021/1843/0/184300a247",
"title": "Assessing the readiness for implementing Business Intelligence system in Vietnam",
"doi": null,
"abstractUrl": "/proceedings-article/snpd-winter/2021/184300a247/1sQKd5belby",
"parentPublication": {
"id": "proceedings/snpd-winter/2021/1843/0",
"title": "2021 21st ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/it/2021/03/09464119",
"title": "Rigorous Data Validation for Accurate Dashboards: Experience From a Higher Education Institution",
"doi": null,
"abstractUrl": "/magazine/it/2021/03/09464119/1uHcqgoeili",
"parentPublication": {
"id": "mags/it",
"title": "IT Professional",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/sc/2022/03/09547788",
"title": "An Empirical Study on How Well Do COVID-19 Information Dashboards Service Users’ Information Needs",
"doi": null,
"abstractUrl": "/journal/sc/2022/03/09547788/1x9Tr00kZH2",
"parentPublication": {
"id": "trans/sc",
"title": "IEEE Transactions on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552200",
"title": "Propagating Visual Designs to Numerous Plots and Dashboards",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552200/1xic4fDV0di",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1q7jpLZLBde",
"title": "2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)",
"acronym": "issrew",
"groupId": "1002972",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1q7jsZHI07u",
"doi": "10.1109/ISSREW51248.2020.00075",
"title": "Declarative Dashboard Generation",
"normalizedTitle": "Declarative Dashboard Generation",
"abstract": "Systems of systems are highly dynamic software systems that require flexible monitoring solutions to be observed and controlled. Indeed, operators have to frequently adapt the set of collected indicators according to changing circumstances, to visualize the behavior of the monitored systems and timely take actions, if needed. Unfortunately, dashboard systems are still quite cumbersome to configure and adapt to a changing set of indicators that must be visualized. This paper reports our initial effort towards the definition of an automatic dashboard generation process that exploits meta-model layouts to create a full dashboard from a set of indicators selected by operators.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Systems of systems are highly dynamic software systems that require flexible monitoring solutions to be observed and controlled. Indeed, operators have to frequently adapt the set of collected indicators according to changing circumstances, to visualize the behavior of the monitored systems and timely take actions, if needed. Unfortunately, dashboard systems are still quite cumbersome to configure and adapt to a changing set of indicators that must be visualized. This paper reports our initial effort towards the definition of an automatic dashboard generation process that exploits meta-model layouts to create a full dashboard from a set of indicators selected by operators.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Systems of systems are highly dynamic software systems that require flexible monitoring solutions to be observed and controlled. Indeed, operators have to frequently adapt the set of collected indicators according to changing circumstances, to visualize the behavior of the monitored systems and timely take actions, if needed. Unfortunately, dashboard systems are still quite cumbersome to configure and adapt to a changing set of indicators that must be visualized. This paper reports our initial effort towards the definition of an automatic dashboard generation process that exploits meta-model layouts to create a full dashboard from a set of indicators selected by operators.",
"fno": "773500a215",
"keywords": [
"System Monitoring",
"Dynamic Software Systems",
"Flexible Monitoring",
"Monitored Systems",
"Automatic Dashboard Generation Process",
"Declarative Dashboard Generation",
"Systems Of Systems",
"System Monitoring",
"Meta Model Layouts",
"Data Visualization",
"Layout",
"Visualization",
"Monitoring",
"Tools",
"Navigation",
"Key Performance Indicator",
"Monitoring Dashboard",
"Dashboard Generation",
"Cloud Monitoring",
"So S Monitoring"
],
"authors": [
{
"affiliation": "University of Milano - Bicocca,Milan,Italy",
"fullName": "Alessandro Tundo",
"givenName": "Alessandro",
"surname": "Tundo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Milano - Bicocca,Milan,Italy",
"fullName": "Chiara Castelnovo",
"givenName": "Chiara",
"surname": "Castelnovo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Milano - Bicocca,Milan,Italy",
"fullName": "Marco Mobilio",
"givenName": "Marco",
"surname": "Mobilio",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Milano - Bicocca,Milan,Italy",
"fullName": "Oliviero Riganelli",
"givenName": "Oliviero",
"surname": "Riganelli",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Milano - Bicocca,Milan,Italy",
"fullName": "Leonardo Mariani",
"givenName": "Leonardo",
"surname": "Mariani",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "issrew",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-10-01T00:00:00",
"pubType": "proceedings",
"pages": "215-218",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-7735-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "773500a209",
"articleId": "1q7jq2YzOEw",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "773500a219",
"articleId": "1q7jqGAKRaM",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/services/2011/4461/0/4461a145",
"title": "Using Traceability to Support SOA Impact Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/services/2011/4461a145/12OmNCdBDDy",
"parentPublication": {
"id": "proceedings/services/2011/4461/0",
"title": "2011 IEEE World Congress on Services",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2017/3870/0/3870a433",
"title": "Dashboard for Monitoring Student Engagement in Mind Mapping Activities",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2017/3870a433/12OmNylsZBd",
"parentPublication": {
"id": "proceedings/icalt/2017/3870/0",
"title": "2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903550",
"title": "Dashboard Design Patterns",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903550/1GZolSVvsPu",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09906971",
"title": "DashBot: Insight-Driven Dashboard Generation Based on Deep Reinforcement Learning",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09906971/1H5EWMQX9ZK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09911200",
"title": "MEDLEY: Intent-based Recommendations to Support Dashboard Composition<sc/>",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09911200/1Hcjm0PMkgw",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/pc/2023/01/10012274",
"title": "Explainable Federated Learning: A Lifecycle Dashboard for Industrial Settings",
"doi": null,
"abstractUrl": "/magazine/pc/2023/01/10012274/1JNmiBno0Le",
"parentPublication": {
"id": "mags/pc",
"title": "IEEE Pervasive Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10057994",
"title": "Dashboard Design Mining and Recommendation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10057994/1LbFmG2HHnW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09035622",
"title": "LADV: Deep Learning Assisted Authoring of Dashboard Visualizations From Images and Sketches",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09035622/1iaeAO11H6o",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vl-hcc/2021/4592/0/09576443",
"title": "PEDI - Piazza Explorer Dashboard for Intervention",
"doi": null,
"abstractUrl": "/proceedings-article/vl-hcc/2021/09576443/1y63pExo97q",
"parentPublication": {
"id": "proceedings/vl-hcc/2021/4592/0",
"title": "2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2021/3851/0/09637388",
"title": "Descriptive Analytics Dashboard for an Inclusive Learning Environment",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2021/09637388/1zuw1NkrZ28",
"parentPublication": {
"id": "proceedings/fie/2021/3851/0",
"title": "2021 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyKJiaV",
"title": "Pattern Recognition, International Conference on",
"acronym": "icpr",
"groupId": "1000545",
"volume": "0",
"displayVolume": "0",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNC8uRhA",
"doi": "10.1109/ICPR.2010.101",
"title": "Dimensionality Reduction for Distributed Vision Systems Using Random Projection",
"normalizedTitle": "Dimensionality Reduction for Distributed Vision Systems Using Random Projection",
"abstract": "Dimensionality reduction is an important issue in the context of distributed vision systems. Processing of dimensionality reduced data requires far less network resources (e.g., storage space, network bandwidth) than processing of original data. In this paper we explore the performance of the random projection method for distributed smart cameras. In our tests, random projection is compared to principal component analysis in terms of recognition efficiency (i.e., object recognition). The results obtained on the COIL-20 image data set show good performance of the random projection in comparison to the principal component analysis, which requires distribution of a subspace and therefore consumes more resources of the network. This indicates that random projection method can elegantly solve the problem of subspace distribution in embedded and distributed vision systems. Moreover, even without explicit orthogonalization or normalization of random projection transformation subspace, the method achieves good object recognition efficiency.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Dimensionality reduction is an important issue in the context of distributed vision systems. Processing of dimensionality reduced data requires far less network resources (e.g., storage space, network bandwidth) than processing of original data. In this paper we explore the performance of the random projection method for distributed smart cameras. In our tests, random projection is compared to principal component analysis in terms of recognition efficiency (i.e., object recognition). The results obtained on the COIL-20 image data set show good performance of the random projection in comparison to the principal component analysis, which requires distribution of a subspace and therefore consumes more resources of the network. This indicates that random projection method can elegantly solve the problem of subspace distribution in embedded and distributed vision systems. Moreover, even without explicit orthogonalization or normalization of random projection transformation subspace, the method achieves good object recognition efficiency.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Dimensionality reduction is an important issue in the context of distributed vision systems. Processing of dimensionality reduced data requires far less network resources (e.g., storage space, network bandwidth) than processing of original data. In this paper we explore the performance of the random projection method for distributed smart cameras. In our tests, random projection is compared to principal component analysis in terms of recognition efficiency (i.e., object recognition). The results obtained on the COIL-20 image data set show good performance of the random projection in comparison to the principal component analysis, which requires distribution of a subspace and therefore consumes more resources of the network. This indicates that random projection method can elegantly solve the problem of subspace distribution in embedded and distributed vision systems. Moreover, even without explicit orthogonalization or normalization of random projection transformation subspace, the method achieves good object recognition efficiency.",
"fno": "4109a380",
"keywords": [
"Dimensionality Reduction",
"Random Projection",
"Distributed Vision Systems"
],
"authors": [
{
"affiliation": null,
"fullName": "Vildana Sulic",
"givenName": "Vildana",
"surname": "Sulic",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Janez Perš",
"givenName": "Janez",
"surname": "Perš",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Matej Kristan",
"givenName": "Matej",
"surname": "Kristan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Stanislav Kovacic",
"givenName": "Stanislav",
"surname": "Kovacic",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-08-01T00:00:00",
"pubType": "proceedings",
"pages": "380-383",
"year": "2010",
"issn": "1051-4651",
"isbn": "978-0-7695-4109-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4109a376",
"articleId": "12OmNwAKCLB",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4109a384",
"articleId": "12OmNB0X8rh",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/asia/2009/3910/0/3910a202",
"title": "Appearance-Based Subspace Projection Techniques for Face Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/asia/2009/3910a202/12OmNANTAyx",
"parentPublication": {
"id": "proceedings/asia/2009/3910/0",
"title": "2009 International Asia Symposium on Intelligent Interaction and Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pcspa/2010/4180/0/4180b107",
"title": "Two-Dimensional Random Projection for Face Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/pcspa/2010/4180b107/12OmNAoDhYL",
"parentPublication": {
"id": "proceedings/pcspa/2010/4180/0",
"title": "Pervasive Computing, Signal Porcessing and Applications, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/gcis/2009/3571/2/3571b509",
"title": "A New Method for Linear Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/gcis/2009/3571b509/12OmNqFrGrQ",
"parentPublication": {
"id": "proceedings/gcis/2009/3571/2",
"title": "2009 WRI Global Congress on Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dbta/2009/3604/0/3604a192",
"title": "A Framework for Semi-supervised Clustering Based on Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/dbta/2009/3604a192/12OmNrF2DMW",
"parentPublication": {
"id": "proceedings/dbta/2009/3604/0",
"title": "2009 First International Workshop on Database Technology and Applications, DBTA",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icapr/2009/3520/0/3520a251",
"title": "Speeding up AdaBoost Classifier with Random Projection",
"doi": null,
"abstractUrl": "/proceedings-article/icapr/2009/3520a251/12OmNwNOaRe",
"parentPublication": {
"id": "proceedings/icapr/2009/3520/0",
"title": "Advances in Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isecs/2009/3643/2/3643b113",
"title": "Multimodal Biometrics Recognition by Dimensionality Reduction Method",
"doi": null,
"abstractUrl": "/proceedings-article/isecs/2009/3643b113/12OmNyQph63",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2009/3804/4/3804e275",
"title": "SVM-Induced Dimensionality Reduction and Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2009/3804e275/12OmNzG4gwg",
"parentPublication": {
"id": "proceedings/icicta/2009/3804/4",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2006/12/k1600",
"title": "Multi-Output Regularized Feature Projection",
"doi": null,
"abstractUrl": "/journal/tk/2006/12/k1600/13rRUILtJzN",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2000/06/i0623",
"title": "Fractional-Step Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tp/2000/06/i0623/13rRUxNmPET",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bracis/2018/8023/0/802300a402",
"title": "Data Classification: Dimensionality Reduction Using Combined and Non-combined Multidimensional Projection Techniques",
"doi": null,
"abstractUrl": "/proceedings-article/bracis/2018/802300a402/17D45X0yjV2",
"parentPublication": {
"id": "proceedings/bracis/2018/8023/0",
"title": "2018 7th Brazilian Conference on Intelligent Systems (BRACIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBDyAaZ",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"acronym": "iccv",
"groupId": "1000149",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNCxtyO4",
"doi": "10.1109/ICCV.2015.128",
"title": "Attribute-Graph: A Graph Based Approach to Image Ranking",
"normalizedTitle": "Attribute-Graph: A Graph Based Approach to Image Ranking",
"abstract": "We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic similarity to a given query image. An Attribute-Graph is an undirected fully connected graph, incorporating both local and global image characteristics. The graph nodes characterise objects as well as the overall scene context using mid-level semantic attributes, while the edges capture the object topology. We demonstrate the effectiveness of Attribute-Graphs by applying them to the problem of image ranking. We benchmark the performance of our algorithm on the 'rPascal' and 'rImageNet' datasets, which we have created in order to evaluate the ranking performance on complex queries containing multiple objects. Our experimental evaluation shows that modelling images as Attribute-Graphs results in improved ranking performance over existing techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic similarity to a given query image. An Attribute-Graph is an undirected fully connected graph, incorporating both local and global image characteristics. The graph nodes characterise objects as well as the overall scene context using mid-level semantic attributes, while the edges capture the object topology. We demonstrate the effectiveness of Attribute-Graphs by applying them to the problem of image ranking. We benchmark the performance of our algorithm on the 'rPascal' and 'rImageNet' datasets, which we have created in order to evaluate the ranking performance on complex queries containing multiple objects. Our experimental evaluation shows that modelling images as Attribute-Graphs results in improved ranking performance over existing techniques.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose a novel image representation, termed Attribute-Graph, to rank images by their semantic similarity to a given query image. An Attribute-Graph is an undirected fully connected graph, incorporating both local and global image characteristics. The graph nodes characterise objects as well as the overall scene context using mid-level semantic attributes, while the edges capture the object topology. We demonstrate the effectiveness of Attribute-Graphs by applying them to the problem of image ranking. We benchmark the performance of our algorithm on the 'rPascal' and 'rImageNet' datasets, which we have created in order to evaluate the ranking performance on complex queries containing multiple objects. Our experimental evaluation shows that modelling images as Attribute-Graphs results in improved ranking performance over existing techniques.",
"fno": "8391b071",
"keywords": [
"Image Edge Detection",
"Semantics",
"Feature Extraction",
"Context",
"Image Representation",
"Image Retrieval",
"Proposals"
],
"authors": [
{
"affiliation": null,
"fullName": "Nikita Prabhu",
"givenName": "Nikita",
"surname": "Prabhu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "R. Venkatesh Babu",
"givenName": "R. Venkatesh",
"surname": "Babu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-12-01T00:00:00",
"pubType": "proceedings",
"pages": "1071-1079",
"year": "2015",
"issn": "2380-7504",
"isbn": "978-1-4673-8391-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "8391b062",
"articleId": "12OmNAXPy4Q",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "8391b080",
"articleId": "12OmNqN6Ral",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2015/8391/0/8391b062",
"title": "Cross-Domain Image Retrieval with a Dual Attribute-Aware Ranking Network",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391b062/12OmNAXPy4Q",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2015/0379/0/0379a160",
"title": "A Novel Unsupervised 2-Stage k-NN Re-Ranking Algorithm for Image Retrieval",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2015/0379a160/12OmNCcKQAW",
"parentPublication": {
"id": "proceedings/ism/2015/0379/0",
"title": "2015 IEEE International Symposium on Multimedia (ISM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdcat/2016/5081/0/07943349",
"title": "Leveraging Click Completion for Graph-Based Image Ranking",
"doi": null,
"abstractUrl": "/proceedings-article/pdcat/2016/07943349/12OmNCgrD2s",
"parentPublication": {
"id": "proceedings/pdcat/2016/5081/0",
"title": "2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2008/2570/0/04607384",
"title": "SocialRank: A ranking model for web image retrieval in web 2.0",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2008/04607384/12OmNs4S8DY",
"parentPublication": {
"id": "proceedings/icme/2008/2570/0",
"title": "2008 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2007/1016/0/04285117",
"title": "Content Based Image Retrieval Using Manifold-Ranking of Blocks",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04285117/12OmNwvVrL6",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2011/0394/0/05995329",
"title": "Image ranking and retrieval based on multi-attribute queries",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2011/05995329/12OmNx9FhNr",
"parentPublication": {
"id": "proceedings/cvpr/2011/0394/0",
"title": "CVPR 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2015/7082/0/07177391",
"title": "Multi-graph multi-instance learning with soft label consistency for object-based image retrieval",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2015/07177391/12OmNxRnvPa",
"parentPublication": {
"id": "proceedings/icme/2015/7082/0",
"title": "2015 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2011/0394/0/05995315",
"title": "Noise resistant graph ranking for improved web image search",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2011/05995315/12OmNzcPAIw",
"parentPublication": {
"id": "proceedings/cvpr/2011/0394/0",
"title": "CVPR 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2011/4520/0/4520a099",
"title": "Retrieval of Envelope Images Using Graph Matching",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2011/4520a099/12OmNzlD9xS",
"parentPublication": {
"id": "proceedings/icdar/2011/4520/0",
"title": "2011 International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2015/01/06512497",
"title": "EMR: A Scalable Graph-Based Ranking Model for Content-Based Image Retrieval",
"doi": null,
"abstractUrl": "/journal/tk/2015/01/06512497/13rRUyfbwr6",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBUAvV8",
"title": "2014 IEEE International Conference on Data Mining Workshop (ICDMW)",
"acronym": "icdmw",
"groupId": "1001620",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyTfg8F",
"doi": "10.1109/ICDMW.2014.153",
"title": "Two-Phase Attribute Ordering for Unsupervised Ranking of Multi-attribute Objects",
"normalizedTitle": "Two-Phase Attribute Ordering for Unsupervised Ranking of Multi-attribute Objects",
"abstract": "Unsupervised ranking faces a problem of distinguishing those critical attributes to ranking. Prior knowledge of ranking might open a new door for this problem. By embedding the ranking prior information, strictly monotonicity and smoothness, this paper presents a two-phase attribute selection procedure for unsupervised ranking. The first phase identifies those irrelevant attributes based on mean Spearman Ranking Correlation Coefficients (SRCCs) of pairs of attributes by knowing that relevant attributes are assumed to be monotone with each other if it is monotone with the ranking score. The second phase carries out Extended Fourier Amplitude Sensitivity Test (EFAST) on a learned ranking rule and provides the total effect for each attribute to ranking. Finally, the most important attribute to ranking are selected to perform ranking. Numerical experiments on synthetical and real datasets illustrate the effectiveness of the two-phase attribute selection for unsupervised ranking.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Unsupervised ranking faces a problem of distinguishing those critical attributes to ranking. Prior knowledge of ranking might open a new door for this problem. By embedding the ranking prior information, strictly monotonicity and smoothness, this paper presents a two-phase attribute selection procedure for unsupervised ranking. The first phase identifies those irrelevant attributes based on mean Spearman Ranking Correlation Coefficients (SRCCs) of pairs of attributes by knowing that relevant attributes are assumed to be monotone with each other if it is monotone with the ranking score. The second phase carries out Extended Fourier Amplitude Sensitivity Test (EFAST) on a learned ranking rule and provides the total effect for each attribute to ranking. Finally, the most important attribute to ranking are selected to perform ranking. Numerical experiments on synthetical and real datasets illustrate the effectiveness of the two-phase attribute selection for unsupervised ranking.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Unsupervised ranking faces a problem of distinguishing those critical attributes to ranking. Prior knowledge of ranking might open a new door for this problem. By embedding the ranking prior information, strictly monotonicity and smoothness, this paper presents a two-phase attribute selection procedure for unsupervised ranking. The first phase identifies those irrelevant attributes based on mean Spearman Ranking Correlation Coefficients (SRCCs) of pairs of attributes by knowing that relevant attributes are assumed to be monotone with each other if it is monotone with the ranking score. The second phase carries out Extended Fourier Amplitude Sensitivity Test (EFAST) on a learned ranking rule and provides the total effect for each attribute to ranking. Finally, the most important attribute to ranking are selected to perform ranking. Numerical experiments on synthetical and real datasets illustrate the effectiveness of the two-phase attribute selection for unsupervised ranking.",
"fno": "4274a175",
"keywords": [
"Correlation",
"Sensitivity Analysis",
"Numerical Models",
"Silicon",
"Interference",
"Frequency Estimation",
"Prior Information Embedding",
"Unsupervised Ranking",
"Multi Attribute",
"Attribute Selection",
"Global Sensitivity Analysis",
"Strict Monotonicity",
"Smoothness"
],
"authors": [
{
"affiliation": null,
"fullName": "Chun-Guo Li",
"givenName": "Chun-Guo",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Xing Mei",
"givenName": "Xing",
"surname": "Mei",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Bao-Gang Hu",
"givenName": "Bao-Gang",
"surname": "Hu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdmw",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-12-01T00:00:00",
"pubType": "proceedings",
"pages": "175-182",
"year": "2014",
"issn": null,
"isbn": "978-1-4799-4274-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4274a167",
"articleId": "12OmNBW0vFL",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4274a183",
"articleId": "12OmNzlD95E",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icde/2016/2020/0/07498407",
"title": "Unsupervised ranking of multi-attribute objects based on principal curves",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2016/07498407/12OmNA0dMP5",
"parentPublication": {
"id": "proceedings/icde/2016/2020/0",
"title": "2016 IEEE 32nd International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2009/3735/5/3735e522",
"title": "An Instance-Based Schema Matching Method with Attributes Ranking and Classification",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2009/3735e522/12OmNBSjITw",
"parentPublication": {
"id": "proceedings/fskd/2009/3735/5",
"title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acsat/2015/0423/0/07478743",
"title": "Using Supervised Attribute Selection for Unsupervised Learning",
"doi": null,
"abstractUrl": "/proceedings-article/acsat/2015/07478743/12OmNBgQFMO",
"parentPublication": {
"id": "proceedings/acsat/2015/0423/0",
"title": "2015 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bwcca/2014/4173/0/4173a566",
"title": "Online/Offline Attribute Based Signature",
"doi": null,
"abstractUrl": "/proceedings-article/bwcca/2014/4173a566/12OmNCcKQNm",
"parentPublication": {
"id": "proceedings/bwcca/2014/4173/0",
"title": "2014 Ninth International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2015/8391/0/8391b071",
"title": "Attribute-Graph: A Graph Based Approach to Image Ranking",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391b071/12OmNCxtyO4",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2011/0394/0/05995329",
"title": "Image ranking and retrieval based on multi-attribute queries",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2011/05995329/12OmNx9FhNr",
"parentPublication": {
"id": "proceedings/cvpr/2011/0394/0",
"title": "CVPR 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2018/4886/0/488601b671",
"title": "Efficient Multi-attribute Similarity Learning Towards Attribute-Based Fashion Search",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2018/488601b671/12OmNyRg4fV",
"parentPublication": {
"id": "proceedings/wacv/2018/4886/0",
"title": "2018 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscmi/2015/9819/0/9819a051",
"title": "Ranking Discrete Multi-attribute Alternatives under Uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/iscmi/2015/9819a051/12OmNzC5STT",
"parentPublication": {
"id": "proceedings/iscmi/2015/9819/0",
"title": "2015 Second International Conference on Soft Computing and Machine Intelligence (ISCMI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2015/12/07118213",
"title": "Unsupervised Ranking of Multi-Attribute Objects Based on Principal Curves",
"doi": null,
"abstractUrl": "/journal/tk/2015/12/07118213/13rRUNvyali",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300b124",
"title": "MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Ranking",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300b124/1FwFxJRvoOc",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J6h4A8ldF6",
"title": "2022 IEEE Visualization and Visual Analytics (VIS)",
"acronym": "vis",
"groupId": "9973064",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J6h8CqzyKc",
"doi": "10.1109/VIS54862.2022.00035",
"title": "Volume Puzzle: visual analysis of segmented volume data with multivariate attributes",
"normalizedTitle": "Volume Puzzle: visual analysis of segmented volume data with multivariate attributes",
"abstract": "A variety of application domains, including material science, neuroscience, and connectomics, commonly use segmented volume data for exploratory visual analysis. In many cases, segmented objects are characterized by multivariate attributes expressing specific geometric or physical features. Objects with similar characteristics, determined by selected attribute configurations, can create peculiar spatial patterns, whose detection and study is of fundamental importance. This task is notoriously difficult, especially when the number of attributes per segment is large. In this work, we propose an interactive framework that combines a state-of-the-art direct volume renderer for categorical volumes with techniques for the analysis of the attribute space and for the automatic creation of 2D transfer function. We show, in particular, how dimensionality reduction, kernel-density estimation, and topological techniques such as Morse analysis combined with scatter and density plots allow the efficient design of two-dimensional color maps that highlight spatial patterns. The capabilities of our framework are demonstrated on synthetic and real-world data from several domains.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A variety of application domains, including material science, neuroscience, and connectomics, commonly use segmented volume data for exploratory visual analysis. In many cases, segmented objects are characterized by multivariate attributes expressing specific geometric or physical features. Objects with similar characteristics, determined by selected attribute configurations, can create peculiar spatial patterns, whose detection and study is of fundamental importance. This task is notoriously difficult, especially when the number of attributes per segment is large. In this work, we propose an interactive framework that combines a state-of-the-art direct volume renderer for categorical volumes with techniques for the analysis of the attribute space and for the automatic creation of 2D transfer function. We show, in particular, how dimensionality reduction, kernel-density estimation, and topological techniques such as Morse analysis combined with scatter and density plots allow the efficient design of two-dimensional color maps that highlight spatial patterns. The capabilities of our framework are demonstrated on synthetic and real-world data from several domains.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A variety of application domains, including material science, neuroscience, and connectomics, commonly use segmented volume data for exploratory visual analysis. In many cases, segmented objects are characterized by multivariate attributes expressing specific geometric or physical features. Objects with similar characteristics, determined by selected attribute configurations, can create peculiar spatial patterns, whose detection and study is of fundamental importance. This task is notoriously difficult, especially when the number of attributes per segment is large. In this work, we propose an interactive framework that combines a state-of-the-art direct volume renderer for categorical volumes with techniques for the analysis of the attribute space and for the automatic creation of 2D transfer function. We show, in particular, how dimensionality reduction, kernel-density estimation, and topological techniques such as Morse analysis combined with scatter and density plots allow the efficient design of two-dimensional color maps that highlight spatial patterns. The capabilities of our framework are demonstrated on synthetic and real-world data from several domains.",
"fno": "881200a130",
"keywords": [
"Data Visualisation",
"Geometry",
"Image Segmentation",
"Rendering Computer Graphics",
"Topology",
"2 D Transfer Function",
"Application Domains",
"Attribute Configurations",
"Attribute Space",
"Categorical Volumes",
"Density Plots",
"Dimensionality Reduction",
"Direct Volume Renderer",
"Exploratory Visual Analysis",
"Geometric Features",
"Interactive Framework",
"Kernel Density Estimation",
"Material Science",
"Morse Analysis",
"Multivariate Attributes",
"Object Segmentation",
"Physical Features",
"Scatter Plots",
"Spatial Patterns",
"Topological Techniques",
"Two Dimensional Color Maps",
"Volume Data Segmentation",
"Volume Puzzle",
"Dimensionality Reduction",
"Neuroscience",
"Visual Analytics",
"Scalability",
"Transfer Functions",
"Estimation",
"Complexity Theory",
"Human Centered Computing",
"Visualization",
"Visualization Techniques",
"Visualization Application Domains",
"Scientific Visualization"
],
"authors": [
{
"affiliation": "Hamad Bin Khalifa University,Qatar",
"fullName": "M. Agus",
"givenName": "M.",
"surname": "Agus",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hamad Bin Khalifa University,Qatar",
"fullName": "A. Aboulhassan",
"givenName": "A.",
"surname": "Aboulhassan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hamad Bin Khalifa University,Qatar",
"fullName": "K. Al Thelaya",
"givenName": "K.",
"surname": "Al Thelaya",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "CRS4,Italy",
"fullName": "G. Pintore",
"givenName": "G.",
"surname": "Pintore",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "CRS4,Italy",
"fullName": "E. Gobbetti",
"givenName": "E.",
"surname": "Gobbetti",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Turin,Italy",
"fullName": "C. Calì",
"givenName": "C.",
"surname": "Calì",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hamad Bin Khalifa University,Qatar",
"fullName": "J. Schneider",
"givenName": "J.",
"surname": "Schneider",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "130-134",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-8812-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1J6h8udlbos",
"name": "pvis202288120-09973193s1-mm_881200a130.zip",
"size": "74.7 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pvis202288120-09973193s1-mm_881200a130.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "881200a125",
"articleId": "1J6hfQGSJj2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "881200a135",
"articleId": "1J6hecX6APm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ldav/2014/5215/0/07013202",
"title": "Multivariate volume visualization through dynamic projections",
"doi": null,
"abstractUrl": "/proceedings-article/ldav/2014/07013202/12OmNrnJ6Xt",
"parentPublication": {
"id": "proceedings/ldav/2014/5215/0",
"title": "2014 IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2008/3357/1/3357a752",
"title": "An Attribute Reduction Algorithm Based on Conditional Entropy and Frequency of Attributes",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2008/3357a752/12OmNxETaaS",
"parentPublication": {
"id": "proceedings/icicta/2008/3357/1",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/prs/1993/4920/0/00586079",
"title": "Segmented ray casting for data parallel volume rendering",
"doi": null,
"abstractUrl": "/proceedings-article/prs/1993/00586079/12OmNybfr4E",
"parentPublication": {
"id": "proceedings/prs/1993/4920/0",
"title": "Proceedings of 1993 IEEE Parallel Rendering Symposium",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875987",
"title": "Attribute Signatures: Dynamic Visual Summaries for Analyzing Multivariate Geographical Data",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875987/13rRUIM2VH2",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192653",
"title": "NeuroBlocks – Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192653/13rRUwh80uC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903343",
"title": "RankAxis: Towards a Systematic Combination of Projection and Ranking in Multi-Attribute Data Exploration",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903343/1GZooOkjYzK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaml/2022/6265/0/626500a068",
"title": "A Hybrid Recommendation Algorithm with Co-embedded Item Attributes and Ratings",
"doi": null,
"abstractUrl": "/proceedings-article/icaml/2022/626500a068/1LkfAMUQfL2",
"parentPublication": {
"id": "proceedings/icaml/2022/6265/0",
"title": "2022 4th International Conference on Applied Machine Learning (ICAML)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a261",
"title": "Visually Exploring Relations Between Structure and Attributes in Multivariate Graphs",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a261/1cMFac4YSGs",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a001",
"title": "Visualization of semantic differential studies with a large number of images, participants and attributes",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a001/1rSR7BFrXjy",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2021/3931/0/393100a051",
"title": "NetScatter: Visual analytics of multivariate time series with a hybrid of dynamic and static variable relationships",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2021/393100a051/1tTtrcoidWg",
"parentPublication": {
"id": "proceedings/pacificvis/2021/3931/0",
"title": "2021 IEEE 14th Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyKJiaj",
"title": "Advances in Computing, Control, and Telecommunication Technologies, International Conference on",
"acronym": "act",
"groupId": "1800014",
"volume": "0",
"displayVolume": "0",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "13bd1sv5Ny3",
"doi": "10.1109/ACT.2009.118",
"title": "Rule Based Reordering and Morphological Processing for English-Malayalam Statistical Machine Translation",
"normalizedTitle": "Rule Based Reordering and Morphological Processing for English-Malayalam Statistical Machine Translation",
"abstract": "In this paper, we mention our work on incorporating rule based reordering and morphological information for English to Malayalam statistical machine translation. The main ideas which have proven very effective are (i) reordering the English source sentence according to Malayalam syntax, and (ii) using the root suffix separation on both English and Malayalam words. The first one is done by applying simple modified transformation rules on the English parse tree, which is given by the Stanford Dependency Parser. The second one is developed by using a morph analyzer. This approach achieves good performance and better results over the phrase-based system. Our approach avoids the use of parsing for the target language (Malayalam), making it suitable for statistical machine translation from English to Malayalam, since parsing tools for Malayalam are currently not available.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we mention our work on incorporating rule based reordering and morphological information for English to Malayalam statistical machine translation. The main ideas which have proven very effective are (i) reordering the English source sentence according to Malayalam syntax, and (ii) using the root suffix separation on both English and Malayalam words. The first one is done by applying simple modified transformation rules on the English parse tree, which is given by the Stanford Dependency Parser. The second one is developed by using a morph analyzer. This approach achieves good performance and better results over the phrase-based system. Our approach avoids the use of parsing for the target language (Malayalam), making it suitable for statistical machine translation from English to Malayalam, since parsing tools for Malayalam are currently not available.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we mention our work on incorporating rule based reordering and morphological information for English to Malayalam statistical machine translation. The main ideas which have proven very effective are (i) reordering the English source sentence according to Malayalam syntax, and (ii) using the root suffix separation on both English and Malayalam words. The first one is done by applying simple modified transformation rules on the English parse tree, which is given by the Stanford Dependency Parser. The second one is developed by using a morph analyzer. This approach achieves good performance and better results over the phrase-based system. Our approach avoids the use of parsing for the target language (Malayalam), making it suitable for statistical machine translation from English to Malayalam, since parsing tools for Malayalam are currently not available.",
"fno": "05376571",
"keywords": [
"Language Translation",
"Statistical Analysis",
"Rule Based Reordering",
"Morphological Processing",
"English Malayalam Statistical Machine Translation",
"Malayalam Syntax",
"English Words",
"Malayalam Words",
"English Parse Tree",
"Stanford Dependency Parser",
"Phrase Based System",
"Surface Mount Technology",
"Natural Languages",
"Computer Networks",
"Telecommunication Computing",
"Roads",
"Dictionaries",
"Telecommunication Control",
"Information Analysis",
"Data Mining",
"Production",
"Phrase Based Model",
"Syntactic Reordering",
"And Morphological Processing"
],
"authors": [
{
"affiliation": null,
"fullName": "Rahul C.",
"givenName": "Rahul",
"surname": "C.",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Dinunath K.",
"givenName": "Dinunath",
"surname": "K.",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Remya Ravindran",
"givenName": "Remya",
"surname": "Ravindran",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "K.P. Soman",
"givenName": "K.P.",
"surname": "Soman",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "act",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-12-01T00:00:00",
"pubType": "proceedings",
"pages": "458-460",
"year": "2009",
"issn": null,
"isbn": "978-1-4244-5321-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05376570",
"articleId": "13bd1fZBGdk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05376564",
"articleId": "13bd1eSlyta",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icacc/2012/4723/0/4723a086",
"title": "Extension Schemes for the Alignment Model of English-Malayalam Statistical Machine Translator",
"doi": null,
"abstractUrl": "/proceedings-article/icacc/2012/4723a086/12OmNBaT5Zt",
"parentPublication": {
"id": "proceedings/icacc/2012/4723/0",
"title": "2012 International Conference on Advances in Computing and Communications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ialp/2009/3904/0/3904a065",
"title": "Improved Reordering Rules for Hierarchical Phrase-Based Translation",
"doi": null,
"abstractUrl": "/proceedings-article/ialp/2009/3904a065/12OmNrAdsCg",
"parentPublication": {
"id": "proceedings/ialp/2009/3904/0",
"title": "Asian Language Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2018/6049/0/604901a340",
"title": "Spelling Errors by Normal and Poor Readers in a Bilingual Malayalam-English Dyslexia Screening Test",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2018/604901a340/12OmNrFBPYC",
"parentPublication": {
"id": "proceedings/icalt/2018/6049/0",
"title": "2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccnea/2017/3981/0/3981a190",
"title": "Learning Better Classification-Based Reordering Model for Phrase-Based Translation",
"doi": null,
"abstractUrl": "/proceedings-article/iccnea/2017/3981a190/12OmNxVlTFE",
"parentPublication": {
"id": "proceedings/iccnea/2017/3981/0",
"title": "2017 International Conference on Computer Network, Electronic and Automation (ICCNEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2013/1309/0/06732647",
"title": "English translation of Chinese pediatrie points: A lost land",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2013/06732647/12OmNy2rS5M",
"parentPublication": {
"id": "proceedings/bibm/2013/1309/0",
"title": "2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/tai/1991/2300/0/00167035",
"title": "AUTOTEC: an English to Chinese machine translation system",
"doi": null,
"abstractUrl": "/proceedings-article/tai/1991/00167035/12OmNyKa5YG",
"parentPublication": {
"id": "proceedings/tai/1991/2300/0",
"title": "1991 Third International Conference on Tools for Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/kse/2012/4760/0/4760a156",
"title": "Sentence Splitting for Vietnamese-English Machine Translation",
"doi": null,
"abstractUrl": "/proceedings-article/kse/2012/4760a156/12OmNyywxCo",
"parentPublication": {
"id": "proceedings/kse/2012/4760/0",
"title": "Knowledge and Systems Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/act/2009/3915/0/05376582",
"title": "Rule Based Machine Translation from English to Malayalam",
"doi": null,
"abstractUrl": "/proceedings-article/act/2009/05376582/13bd1fZBGcd",
"parentPublication": {
"id": "proceedings/act/2009/3915/0",
"title": "Advances in Computing, Control, and Telecommunication Technologies, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itc/2010/3975/0/05460577",
"title": "SVM Based Part of Speech Tagger for Malayalam",
"doi": null,
"abstractUrl": "/proceedings-article/itc/2010/05460577/13bd1tl2omC",
"parentPublication": {
"id": "proceedings/itc/2010/3975/0",
"title": "2010 International Conference on Recent Trends in Information, Telecommunication and Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsgea/2021/3263/0/326300a185",
"title": "Chinese English translation accuracy detection method based on machine learning",
"doi": null,
"abstractUrl": "/proceedings-article/icsgea/2021/326300a185/1vb9eaoBMBO",
"parentPublication": {
"id": "proceedings/icsgea/2021/3263/0",
"title": "2021 6th International Conference on Smart Grid and Electrical Automation (ICSGEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKiqH",
"title": "2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA)",
"acronym": "bdva",
"groupId": "1809805",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45WYQJ8j",
"doi": "10.1109/BDVA.2018.8533892",
"title": "Axes and Coordinate Systems Representations for Immersive Analytics of Multi-Dimensional Data",
"normalizedTitle": "Axes and Coordinate Systems Representations for Immersive Analytics of Multi-Dimensional Data",
"abstract": "Axes are the main components of coordinate systems representations. They play a critical role for the visual analysis of multi-dimensional data. However their representation seems to have always be considered self evident, with oriented lines crossing at an origin, completed with labels such as ticks and names. Such classical representation show limits when it comes 3D visualization and immersive analytic (IA), mainly because orthogonal projection of points on linear axes is hard in a 3d environment, and because the user can move therefore the axes can get out of his field of view. In this paper we propose a task-based definition of axes and coordinate systems representation, as well as a tentative design space for coordinates systems representation in immersion. We also present an exploratory user study we carried out to compare three grid-based representations of coordinate systems for multidimensional data analysis with 3D scatterplots.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Axes are the main components of coordinate systems representations. They play a critical role for the visual analysis of multi-dimensional data. However their representation seems to have always be considered self evident, with oriented lines crossing at an origin, completed with labels such as ticks and names. Such classical representation show limits when it comes 3D visualization and immersive analytic (IA), mainly because orthogonal projection of points on linear axes is hard in a 3d environment, and because the user can move therefore the axes can get out of his field of view. In this paper we propose a task-based definition of axes and coordinate systems representation, as well as a tentative design space for coordinates systems representation in immersion. We also present an exploratory user study we carried out to compare three grid-based representations of coordinate systems for multidimensional data analysis with 3D scatterplots.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Axes are the main components of coordinate systems representations. They play a critical role for the visual analysis of multi-dimensional data. However their representation seems to have always be considered self evident, with oriented lines crossing at an origin, completed with labels such as ticks and names. Such classical representation show limits when it comes 3D visualization and immersive analytic (IA), mainly because orthogonal projection of points on linear axes is hard in a 3d environment, and because the user can move therefore the axes can get out of his field of view. In this paper we propose a task-based definition of axes and coordinate systems representation, as well as a tentative design space for coordinates systems representation in immersion. We also present an exploratory user study we carried out to compare three grid-based representations of coordinate systems for multidimensional data analysis with 3D scatterplots.",
"fno": "08533892",
"keywords": [
"Data Visualization",
"Task Analysis",
"Three Dimensional Displays",
"Two Dimensional Displays",
"Data Analysis",
"Proposals",
"Semantics"
],
"authors": [
{
"affiliation": null,
"fullName": "Adrien Fonnet",
"givenName": "Adrien",
"surname": "Fonnet",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Toinon Vigier",
"givenName": "Toinon",
"surname": "Vigier",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Yannick Prie",
"givenName": "Yannick",
"surname": "Prie",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Gregoire Cliquet",
"givenName": "Gregoire",
"surname": "Cliquet",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Fabien Picarougne",
"givenName": "Fabien",
"surname": "Picarougne",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bdva",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-10",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-9194-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08533891",
"articleId": "17D45WKWnJP",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08533893",
"articleId": "17D45Wuc3a3",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "trans/tg/2013/12/ttg2013122615",
"title": "Orthographic Star Coordinates",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122615/13rRUILLkDP",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08546220",
"title": "Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08546220/17D45WHONmO",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904437",
"title": "PC-Expo: A Metrics-Based Interactive Axes Reordering Method for Parallel Coordinate Displays",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904437/1H1gnemxdqE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2019/9552/0/955200a314",
"title": "A Light-Weighted Network for Facial Landmark Detection via Combined Heatmap and Coordinate Regression",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2019/955200a314/1cdOPysKPuw",
"parentPublication": {
"id": "proceedings/icme/2019/9552/0",
"title": "2019 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300i637",
"title": "FrameNet: Learning Local Canonical Frames of 3D Surfaces From a Single RGB Image",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300i637/1hVlGmjtYLC",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300e530",
"title": "Texture Fields: Learning Texture Representations in Function Space",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300e530/1hVlndN3Szm",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2020/5608/0/09089446",
"title": "Graphical Perception for Immersive Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2020/09089446/1jIxfA3tlUk",
"parentPublication": {
"id": "proceedings/vr/2020/5608/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800l1980",
"title": "Hierarchical Scene Coordinate Classification and Regression for Visual Localization",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800l1980/1m3nLD67F3q",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2020/8128/0/812800a423",
"title": "Semantic Implicit Neural Scene Representations With Semi-Supervised Training",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2020/812800a423/1qyxoFrZU88",
"parentPublication": {
"id": "proceedings/3dv/2020/8128/0",
"title": "2020 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900c845",
"title": "Learned Initializations for Optimizing Coordinate-Based Neural Representations",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900c845/1yeIp77tBPG",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1IT0z7XBBgA",
"title": "2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV)",
"acronym": "ldav",
"groupId": "9966414",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1IT0C1KMUmc",
"doi": "10.1109/LDAV57265.2022.9966393",
"title": "Angular-based Edge Bundled Parallel Coordinates Plot for the Visual Analysis of Large Ensemble Simulation Data",
"normalizedTitle": "Angular-based Edge Bundled Parallel Coordinates Plot for the Visual Analysis of Large Ensemble Simulation Data",
"abstract": "With the continuous increase in the computational power and resources of modern high-performance computing (HPC) systems, large-scale ensemble simulations have become widely used in various fields of science and engineering, and especially in meteoro-logical and climate science. It is widely known that the simulation outputs are large time-varying, multivariate, and multivalued datasets which pose a particular challenge to the visualization and analysis tasks. In this work, we focused on the widely used Parallel Coordinates Plot (PCP) to analyze the interrelations between different parameters, such as variables, among the members. However, PCP may suffer from visual cluttering and drawing performance with the increase on the data size to be analyzed, that is, the number of polylines. To overcome this problem, we present an extension to the PCP by adding Bézier curves connecting the angular distribution plots representing the mean and variance of the inclination of the line segments between parallel axes. The proposed Angular-based Parallel Coordinates Plot (APCP) is capable of presenting a simplified overview of the entire ensemble data set while maintaining the correlation information between the adjacent variables. To verify its effectiveness, we developed a visual analytics prototype system and evaluated by using a meteorological ensemble simulation output from the supercomputer Fugaku.",
"abstracts": [
{
"abstractType": "Regular",
"content": "With the continuous increase in the computational power and resources of modern high-performance computing (HPC) systems, large-scale ensemble simulations have become widely used in various fields of science and engineering, and especially in meteoro-logical and climate science. It is widely known that the simulation outputs are large time-varying, multivariate, and multivalued datasets which pose a particular challenge to the visualization and analysis tasks. In this work, we focused on the widely used Parallel Coordinates Plot (PCP) to analyze the interrelations between different parameters, such as variables, among the members. However, PCP may suffer from visual cluttering and drawing performance with the increase on the data size to be analyzed, that is, the number of polylines. To overcome this problem, we present an extension to the PCP by adding Bézier curves connecting the angular distribution plots representing the mean and variance of the inclination of the line segments between parallel axes. The proposed Angular-based Parallel Coordinates Plot (APCP) is capable of presenting a simplified overview of the entire ensemble data set while maintaining the correlation information between the adjacent variables. To verify its effectiveness, we developed a visual analytics prototype system and evaluated by using a meteorological ensemble simulation output from the supercomputer Fugaku.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "With the continuous increase in the computational power and resources of modern high-performance computing (HPC) systems, large-scale ensemble simulations have become widely used in various fields of science and engineering, and especially in meteoro-logical and climate science. It is widely known that the simulation outputs are large time-varying, multivariate, and multivalued datasets which pose a particular challenge to the visualization and analysis tasks. In this work, we focused on the widely used Parallel Coordinates Plot (PCP) to analyze the interrelations between different parameters, such as variables, among the members. However, PCP may suffer from visual cluttering and drawing performance with the increase on the data size to be analyzed, that is, the number of polylines. To overcome this problem, we present an extension to the PCP by adding Bézier curves connecting the angular distribution plots representing the mean and variance of the inclination of the line segments between parallel axes. The proposed Angular-based Parallel Coordinates Plot (APCP) is capable of presenting a simplified overview of the entire ensemble data set while maintaining the correlation information between the adjacent variables. To verify its effectiveness, we developed a visual analytics prototype system and evaluated by using a meteorological ensemble simulation output from the supercomputer Fugaku.",
"fno": "09966393",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Parallel Processing",
"Angular Distribution Plots",
"Angular Based Parallel Coordinates Plot",
"Climate Science",
"Computational Power",
"Ensemble Simulation Data",
"Entire Ensemble Data",
"Large Scale Ensemble Simulations",
"Meteoro Logical",
"Meteorological Ensemble Simulation Output",
"Modern High Performance Computing Systems",
"Multivalued Datasets",
"PCP",
"Simulation Outputs",
"Time Varying",
"Visual Analytics Prototype System",
"Visual Cluttering",
"Visualization",
"Analytical Models",
"Correlation",
"Computational Modeling",
"Visual Analytics",
"Data Visualization",
"Prototypes",
"Data Models",
"Human Centered Computing Visualization Visualization Techniques",
"Human Centered Computing Visualization Application Domains Visual Analytics"
],
"authors": [
{
"affiliation": "Kobe University",
"fullName": "Keita Watanabe",
"givenName": "Keita",
"surname": "Watanabe",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Kobe University",
"fullName": "Naohisa Sakamoto",
"givenName": "Naohisa",
"surname": "Sakamoto",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "RIKEN R-CCS",
"fullName": "Jorji Nonaka",
"givenName": "Jorji",
"surname": "Nonaka",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "RIKEN R-CCS",
"fullName": "Yasumitsu Maejima",
"givenName": "Yasumitsu",
"surname": "Maejima",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ldav",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-10",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-9156-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1IT0B7sxaYU",
"name": "pldav202291560-09966393s1-paper5_1006_multimedia.zip",
"size": "111 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pldav202291560-09966393s1-paper5_1006_multimedia.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09966394",
"articleId": "1IT0D2NIYAE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09966396",
"articleId": "1IT0zi0WIUg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-infovis/2002/1751/0/17510127",
"title": "Angular Brushing of Extended Parallel Coordinates",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/2002/17510127/12OmNzYNNf3",
"parentPublication": {
"id": "proceedings/ieee-infovis/2002/1751/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013122606",
"title": "GPLOM: The Generalized Plot Matrix for Visualizing Multidimensional Multivariate Data",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122606/13rRUxAAT0S",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539323",
"title": "Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539323/13rRUxNEqPZ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440102",
"title": "EnsembleLens: Ensemble-based Visual Exploration of Anomaly Detection Algorithms with Multidimensional Data",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440102/17D45VsBU48",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2022/9007/0/900700a114",
"title": "Comparative evaluation of the Scatter Plot Matrix and Parallel Coordinates Plot Matrix",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2022/900700a114/1KaFNhzetSo",
"parentPublication": {
"id": "proceedings/iv/2022/9007/0",
"title": "2022 26th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/07/09262081",
"title": "Augmenting Parallel Coordinates Plots With Color-Coded Stacked Histograms",
"doi": null,
"abstractUrl": "/journal/tg/2022/07/09262081/1oPzTTEZFyE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/10/09362264",
"title": "Visual Analysis of Multi-Parameter Distributions Across Ensembles of 3D Fields",
"doi": null,
"abstractUrl": "/journal/tg/2022/10/09362264/1rtTH3Jlh72",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412241",
"title": "Fixed simplex coordinates for angular margin loss in CapsNet",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412241/1tmiWUEh41W",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2023/01/09599491",
"title": "Visual Analysis of Multidimensional Big Data: A Scalable Lightweight Bundling Method for Parallel Coordinates",
"doi": null,
"abstractUrl": "/journal/bd/2023/01/09599491/1yeC5mmD996",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vahc/2021/2067/0/206700a001",
"title": "COVID-19 EnsembleVis: Visual Analysis of County-Level Ensemble Forecast Models",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2021/206700a001/1z0yltnU46I",
"parentPublication": {
"id": "proceedings/vahc/2021/2067/0",
"title": "2021 IEEE Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1jPb3itzOTK",
"title": "2020 3rd International Conference on Information and Computer Technologies (ICICT)",
"acronym": "icict",
"groupId": "1825584",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1jPb5kxsLsc",
"doi": "10.1109/ICICT50521.2020.00008",
"title": "Partial Scoring of Reordering Tasks Revisited: Linearity Matrix by Excel",
"normalizedTitle": "Partial Scoring of Reordering Tasks Revisited: Linearity Matrix by Excel",
"abstract": "Estimating a partial score of item reordering tasks has long been neglected in language testing and education sciences. A psychologically valid means of scoring, MRS (Maximal Relative Sequence) was proposed by the author and transplanted to Excel. As the protocol simply picks up elements in relative ascending order, it made easier the non-specialists' access to and analysis of the calculation process resulting in educational as well as practical significance. However, since the Excel enumeration replicated each step of MRS precisely, the number of columns consumed explodes as the number of elements increases. Moreover, MRS merely counts the number of elements to be relocated; it fails to consider the distance of relocation for recovery. This paper proposes an alternative solution LM (Linearity Matrix), also executable with Excel's basic functions, with far fewer columns to consume. Further, LM is advantageous over MRS in that it is a general protocol of estimating relative similarity of two sequences of which Kendall's tau is a special case; LM is adjustable as to the degree of adjacency constraint by changing the distance weight for all combinations of elements.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Estimating a partial score of item reordering tasks has long been neglected in language testing and education sciences. A psychologically valid means of scoring, MRS (Maximal Relative Sequence) was proposed by the author and transplanted to Excel. As the protocol simply picks up elements in relative ascending order, it made easier the non-specialists' access to and analysis of the calculation process resulting in educational as well as practical significance. However, since the Excel enumeration replicated each step of MRS precisely, the number of columns consumed explodes as the number of elements increases. Moreover, MRS merely counts the number of elements to be relocated; it fails to consider the distance of relocation for recovery. This paper proposes an alternative solution LM (Linearity Matrix), also executable with Excel's basic functions, with far fewer columns to consume. Further, LM is advantageous over MRS in that it is a general protocol of estimating relative similarity of two sequences of which Kendall's tau is a special case; LM is adjustable as to the degree of adjacency constraint by changing the distance weight for all combinations of elements.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Estimating a partial score of item reordering tasks has long been neglected in language testing and education sciences. A psychologically valid means of scoring, MRS (Maximal Relative Sequence) was proposed by the author and transplanted to Excel. As the protocol simply picks up elements in relative ascending order, it made easier the non-specialists' access to and analysis of the calculation process resulting in educational as well as practical significance. However, since the Excel enumeration replicated each step of MRS precisely, the number of columns consumed explodes as the number of elements increases. Moreover, MRS merely counts the number of elements to be relocated; it fails to consider the distance of relocation for recovery. This paper proposes an alternative solution LM (Linearity Matrix), also executable with Excel's basic functions, with far fewer columns to consume. Further, LM is advantageous over MRS in that it is a general protocol of estimating relative similarity of two sequences of which Kendall's tau is a special case; LM is adjustable as to the degree of adjacency constraint by changing the distance weight for all combinations of elements.",
"fno": "728300a001",
"keywords": [
"Educational Computing",
"Matrix Algebra",
"Psychology",
"Partial Scoring",
"Linearity Matrix",
"Partial Score",
"Item Reordering Tasks",
"Language Testing",
"Education Sciences",
"Maximal Relative Sequence",
"Relative Ascending Order",
"Calculation Process",
"Excel Enumeration",
"Excels Basic Functions",
"Relative Similarity",
"Educational As Well As Practical Significance",
"Kendalls Tau",
"Linearity",
"Task Analysis",
"Protocols",
"Computers",
"Switches",
"Testing",
"Education",
"Reordering",
"Partial Scoring",
"Recovery Distance",
"Kendall X 2019 S Tau",
"Excel"
],
"authors": [
{
"affiliation": "Dokkyo University, Japan",
"fullName": "Amma Kazuo",
"givenName": "Amma",
"surname": "Kazuo",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icict",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-03-01T00:00:00",
"pubType": "proceedings",
"pages": "1-6",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-7283-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "728300z019",
"articleId": "1jPgX6gCEr6",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "728300a007",
"articleId": "1jPb6g7LnvG",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ipdpsw/2014/4116/0/4116a671",
"title": "WECPAR: List Ranking Algorithm and Relative Computational Power",
"doi": null,
"abstractUrl": "/proceedings-article/ipdpsw/2014/4116a671/12OmNyO8tTg",
"parentPublication": {
"id": "proceedings/ipdpsw/2014/4116/0",
"title": "2014 IEEE International Parallel & Distributed Processing Symposium Workshops (IPDPSW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2016/03/07103344",
"title": "Dual-Calibration Technique for Improving Static Linearity of Thermometer DACs for I/O",
"doi": null,
"abstractUrl": "/journal/si/2016/03/07103344/13rRUxBJhsO",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2015/12/07005507",
"title": "Improving the linearity and power efficiency of active switched-capacitor filters in a compact die area",
"doi": null,
"abstractUrl": "/journal/si/2015/12/07005507/13rRUxlgy1v",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aivr/2018/9269/0/926900a185",
"title": "AI for Toggling the Linearity of Interactions in AR",
"doi": null,
"abstractUrl": "/proceedings-article/aivr/2018/926900a185/17D45Wda7fy",
"parentPublication": {
"id": "proceedings/aivr/2018/9269/0",
"title": "2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2018/8308/0/830800a318",
"title": "Research on Generating Three Stage Data of Both Sides in Table Tennis Competition with Excel",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2018/830800a318/17D45XtvpdB",
"parentPublication": {
"id": "proceedings/icicta/2018/8308/0",
"title": "2018 11th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNqH9hnp",
"title": "2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyQYtqF",
"doi": "10.1109/CVPR.2016.15",
"title": "Latent Embeddings for Zero-Shot Classification",
"normalizedTitle": "Latent Embeddings for Zero-Shot Classification",
"abstract": "We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero-shot classification. The proposed method augments the state-of-the-art bilinear compatibility model by incorporating latent variables. Instead of learning a single bilinear map, it learns a collection of maps with the selection, of which map to use, being a latent variable for the current image-class pair. We train the model with a ranking based objective function which penalizes incorrect rankings of the true class for a given image. We empirically demonstrate that our model improves the state-of-the-art for various class embeddings consistently on three challenging publicly available datasets for the zero-shot setting. Moreover, our method leads to visually highly interpretable results with clear clusters of different fine-grained object properties that correspond to different latent variable maps.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero-shot classification. The proposed method augments the state-of-the-art bilinear compatibility model by incorporating latent variables. Instead of learning a single bilinear map, it learns a collection of maps with the selection, of which map to use, being a latent variable for the current image-class pair. We train the model with a ranking based objective function which penalizes incorrect rankings of the true class for a given image. We empirically demonstrate that our model improves the state-of-the-art for various class embeddings consistently on three challenging publicly available datasets for the zero-shot setting. Moreover, our method leads to visually highly interpretable results with clear clusters of different fine-grained object properties that correspond to different latent variable maps.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero-shot classification. The proposed method augments the state-of-the-art bilinear compatibility model by incorporating latent variables. Instead of learning a single bilinear map, it learns a collection of maps with the selection, of which map to use, being a latent variable for the current image-class pair. We train the model with a ranking based objective function which penalizes incorrect rankings of the true class for a given image. We empirically demonstrate that our model improves the state-of-the-art for various class embeddings consistently on three challenging publicly available datasets for the zero-shot setting. Moreover, our method leads to visually highly interpretable results with clear clusters of different fine-grained object properties that correspond to different latent variable maps.",
"fno": "8851a069",
"keywords": [
"Visualization",
"Training",
"Computational Modeling",
"Deformable Models",
"Computer Vision",
"Context Modeling",
"Birds"
],
"authors": [
{
"affiliation": null,
"fullName": "Yongqin Xian",
"givenName": "Yongqin",
"surname": "Xian",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Zeynep Akata",
"givenName": "Zeynep",
"surname": "Akata",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Gaurav Sharma",
"givenName": "Gaurav",
"surname": "Sharma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Quynh Nguyen",
"givenName": "Quynh",
"surname": "Nguyen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Matthias Hein",
"givenName": "Matthias",
"surname": "Hein",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Bernt Schiele",
"givenName": "Bernt",
"surname": "Schiele",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-06-01T00:00:00",
"pubType": "proceedings",
"pages": "69-77",
"year": "2016",
"issn": "1063-6919",
"isbn": "978-1-4673-8851-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "8851a059",
"articleId": "12OmNBcAGKE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "8851a078",
"articleId": "12OmNvrdHZO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2017/1032/0/08237715",
"title": "Learning Discriminative Latent Attributes for Zero-Shot Classification",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/08237715/12OmNy6qfNL",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2017/0457/0/0457g412",
"title": "Gaze Embeddings for Zero-Shot Image Classification",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457g412/12OmNyqiaRm",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200j919",
"title": "Learning Compatible Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200j919/1BmFnvEWa7m",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200i382",
"title": "Binocular Mutual Learning for Improving Few-shot Classification",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200i382/1BmGaPdsx5S",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2022/8739/0/873900d930",
"title": "Zero-shot Learning Using Multimodal Descriptions",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2022/873900d930/1G56OtiHKUg",
"parentPublication": {
"id": "proceedings/cvprw/2022/8739/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2022/8739/0/873900e588",
"title": "Semantically Grounded Visual Embeddings for Zero-Shot Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2022/873900e588/1G56ddEn8D6",
"parentPublication": {
"id": "proceedings/cvprw/2022/8739/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600j306",
"title": "VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600j306/1H1j2mN3nuE",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2019/3293/0/329300i239",
"title": "Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2019/329300i239/1gyrjOx3dII",
"parentPublication": {
"id": "proceedings/cvpr/2019/3293/0",
"title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300h424",
"title": "ViCo: Word Embeddings From Visual Co-Occurrences",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300h424/1hQqhuUL5i8",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700d089",
"title": "AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700d089/1uqGnsJoVs4",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNz5JC0v",
"title": "2010 International Conference on Digital Image Computing: Techniques and Applications",
"acronym": "dicta",
"groupId": "1001512",
"volume": "0",
"displayVolume": "0",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNxwWoRF",
"doi": "10.1109/DICTA.2010.66",
"title": "Robust Dimensionality Reduction for Human Action Recognition",
"normalizedTitle": "Robust Dimensionality Reduction for Human Action Recognition",
"abstract": "Human action recognition can be approached by combining an action-discriminative feature set with a classifier. However, the dimensionality of typical feature sets joint with that of the time dimension often leads to a curse-of-dimensionality situation. Moreover, the measurement of the feature set is subject to sometime severe errors. This paper presents an approach to human action recognition based on robust dimensionality reduction. The observation probabilities of hidden Markov models (HMM) are modelled by mixtures of probabilistic principal components analyzers and mixtures of Z_$t$_Z-distribution sub-spaces, and compared with conventional Gaussian mixture models. Experimental results on two datasets show that dimensionality reduction helps improve the classification accuracy and that the heavier-tailed Z_$t$_Z-distribution can help reduce the impact of outliers generated by segmentation errors.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Human action recognition can be approached by combining an action-discriminative feature set with a classifier. However, the dimensionality of typical feature sets joint with that of the time dimension often leads to a curse-of-dimensionality situation. Moreover, the measurement of the feature set is subject to sometime severe errors. This paper presents an approach to human action recognition based on robust dimensionality reduction. The observation probabilities of hidden Markov models (HMM) are modelled by mixtures of probabilistic principal components analyzers and mixtures of $t$-distribution sub-spaces, and compared with conventional Gaussian mixture models. Experimental results on two datasets show that dimensionality reduction helps improve the classification accuracy and that the heavier-tailed $t$-distribution can help reduce the impact of outliers generated by segmentation errors.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Human action recognition can be approached by combining an action-discriminative feature set with a classifier. However, the dimensionality of typical feature sets joint with that of the time dimension often leads to a curse-of-dimensionality situation. Moreover, the measurement of the feature set is subject to sometime severe errors. This paper presents an approach to human action recognition based on robust dimensionality reduction. The observation probabilities of hidden Markov models (HMM) are modelled by mixtures of probabilistic principal components analyzers and mixtures of --distribution sub-spaces, and compared with conventional Gaussian mixture models. Experimental results on two datasets show that dimensionality reduction helps improve the classification accuracy and that the heavier-tailed --distribution can help reduce the impact of outliers generated by segmentation errors.",
"fno": "4271a349",
"keywords": [
"Action Recognition",
"Dimensionality Reduction",
"HMM"
],
"authors": [
{
"affiliation": null,
"fullName": "Oscar Perez Concha",
"givenName": "Oscar Perez",
"surname": "Concha",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Richard Yi Da Xu",
"givenName": "Richard Yi Da",
"surname": "Xu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Massimo Piccardi",
"givenName": "Massimo",
"surname": "Piccardi",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dicta",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-12-01T00:00:00",
"pubType": "proceedings",
"pages": "349-356",
"year": "2010",
"issn": null,
"isbn": "978-0-7695-4271-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4271a343",
"articleId": "12OmNx3HI8o",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4271a357",
"articleId": "12OmNBlXs2p",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ijcbs/2009/3739/0/3739a533",
"title": "A Novel Nonlinear Dimensionality Reduction Method for Robust Wood Image Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/ijcbs/2009/3739a533/12OmNB8kHXF",
"parentPublication": {
"id": "proceedings/ijcbs/2009/3739/0",
"title": "2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing (IJCBS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/avss/2012/4797/0/4797a130",
"title": "Analyzing the Subspaces Obtained by Dimensionality Reduction for Human Action Recognition from 3d Data",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2012/4797a130/12OmNBscCXK",
"parentPublication": {
"id": "proceedings/avss/2012/4797/0",
"title": "2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2008/3305/2/3305b048",
"title": "Unsupervised Sequential Forward Dimensionality Reduction Based on Fractal",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2008/3305b048/12OmNxymo5k",
"parentPublication": {
"id": "fskd/2008/3305/2",
"title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2011/4596/0/4596a865",
"title": "Transferable Discriminative Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2011/4596a865/12OmNy3iFuF",
"parentPublication": {
"id": "proceedings/ictai/2011/4596/0",
"title": "2011 IEEE 23rd International Conference on Tools with Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccgi/2008/3275/0/3275a160",
"title": "Dimensionality Reduction for Feature and Pattern Selection in Classification Problems",
"doi": null,
"abstractUrl": "/proceedings-article/iccgi/2008/3275a160/12OmNyeWdHs",
"parentPublication": {
"id": "proceedings/iccgi/2008/3275/0",
"title": "Computing in the Global Information Technology, International Multi-Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2007/12/i2143",
"title": "Orthogonal Neighborhood Preserving Projections: A Projection-Based Dimensionality Reduction Technique",
"doi": null,
"abstractUrl": "/journal/tp/2007/12/i2143/13rRUwbaqVU",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2000/06/i0623",
"title": "Fractional-Step Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tp/2000/06/i0623/13rRUxNmPET",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1989/03/i0304",
"title": "Dimensionality-Reduction Using Connectionist Networks",
"doi": null,
"abstractUrl": "/journal/tp/1989/03/i0304/13rRUxYrbN7",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08546311",
"title": "IMU-Based Robust Human Activity Recognition using Feature Analysis, Extraction, and Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08546311/17D45Wt3Exr",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2019/5686/0/568600a577",
"title": "Autoencoder Based Dimensionality Reduction of Feature Vectors for Object Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2019/568600a577/1j9xB188lAk",
"parentPublication": {
"id": "proceedings/sitis/2019/5686/0",
"title": "2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxFJXD8",
"title": "2011 IEEE 23rd International Conference on Tools with Artificial Intelligence",
"acronym": "ictai",
"groupId": "1000763",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNy3iFuF",
"doi": "10.1109/ICTAI.2011.134",
"title": "Transferable Discriminative Dimensionality Reduction",
"normalizedTitle": "Transferable Discriminative Dimensionality Reduction",
"abstract": "In transfer learning scenarios, previous discriminative dimensionality reduction methods tend to perform poorly owing to the difference between source and target distributions. In such cases, it is unsuitable to only consider discrimination in the low-dimensional source latent space since this would generalize badly to target domains. In this paper, we propose a new dimensionality reduction method for transfer learning scenarios, which is called transferable discriminative dimensionality reduction (TDDR). By resolving an objective function that encourages the separation of the domain-merged data and penalizes the distance between source and target distributions, we can find a low-dimensional latent space which guarantees not only the discrimination of projected samples, but also the transferability to enable later classification or regression models constructed in the source domain to generalize well to the target domain. In the experiments, we firstly analyze the perspective of transfer learning in brain-computer interface (BCI) research and then test TDDR on two real datasets from BCI applications. The experimental results show that the TDDR method can learn a low-dimensional latent feature space where the source models can perform well in the target domain.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In transfer learning scenarios, previous discriminative dimensionality reduction methods tend to perform poorly owing to the difference between source and target distributions. In such cases, it is unsuitable to only consider discrimination in the low-dimensional source latent space since this would generalize badly to target domains. In this paper, we propose a new dimensionality reduction method for transfer learning scenarios, which is called transferable discriminative dimensionality reduction (TDDR). By resolving an objective function that encourages the separation of the domain-merged data and penalizes the distance between source and target distributions, we can find a low-dimensional latent space which guarantees not only the discrimination of projected samples, but also the transferability to enable later classification or regression models constructed in the source domain to generalize well to the target domain. In the experiments, we firstly analyze the perspective of transfer learning in brain-computer interface (BCI) research and then test TDDR on two real datasets from BCI applications. The experimental results show that the TDDR method can learn a low-dimensional latent feature space where the source models can perform well in the target domain.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In transfer learning scenarios, previous discriminative dimensionality reduction methods tend to perform poorly owing to the difference between source and target distributions. In such cases, it is unsuitable to only consider discrimination in the low-dimensional source latent space since this would generalize badly to target domains. In this paper, we propose a new dimensionality reduction method for transfer learning scenarios, which is called transferable discriminative dimensionality reduction (TDDR). By resolving an objective function that encourages the separation of the domain-merged data and penalizes the distance between source and target distributions, we can find a low-dimensional latent space which guarantees not only the discrimination of projected samples, but also the transferability to enable later classification or regression models constructed in the source domain to generalize well to the target domain. In the experiments, we firstly analyze the perspective of transfer learning in brain-computer interface (BCI) research and then test TDDR on two real datasets from BCI applications. The experimental results show that the TDDR method can learn a low-dimensional latent feature space where the source models can perform well in the target domain.",
"fno": "4596a865",
"keywords": [
"Dimensionality Reduction",
"Fisher Discriminant Analysis",
"Transfer Learning",
"Brain Computer Interface"
],
"authors": [
{
"affiliation": null,
"fullName": "Wenting Tu",
"givenName": "Wenting",
"surname": "Tu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Shiliang Sun",
"givenName": "Shiliang",
"surname": "Sun",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ictai",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2011-11-01T00:00:00",
"pubType": "proceedings",
"pages": "865-868",
"year": "2011",
"issn": "1082-3409",
"isbn": "978-0-7695-4596-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4596a856",
"articleId": "12OmNyRxFty",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4596a869",
"articleId": "12OmNzBOhYc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/gcis/2009/3571/2/3571b509",
"title": "A New Method for Linear Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/gcis/2009/3571b509/12OmNqFrGrQ",
"parentPublication": {
"id": "proceedings/gcis/2009/3571/2",
"title": "2009 WRI Global Congress on Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscsct/2008/3498/2/3498b281",
"title": "The Dimensionality Reduction of Feature Vectors by Generalized Cross Product",
"doi": null,
"abstractUrl": "/proceedings-article/iscsct/2008/3498b281/12OmNsd6viB",
"parentPublication": {
"id": "proceedings/iscsct/2008/3498/1",
"title": "2008 International Symposium on Computer Science and Computational Technology (ISCSCT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2010/4257/0/4257b159",
"title": "Efficient Dimensionality Reduction on Undersampled Problems through Incremental Discriminative Common Vectors",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2010/4257b159/12OmNx9FhN9",
"parentPublication": {
"id": "proceedings/icdmw/2010/4257/0",
"title": "2010 IEEE International Conference on Data Mining Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2011/4607/1/4607a275",
"title": "Dimensionality Reduction by Unsupervised K-Nearest Neighbor Regression",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2011/4607a275/12OmNxWLTmw",
"parentPublication": {
"id": "proceedings/icmla/2011/4607/1",
"title": "Machine Learning and Applications, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2009/3804/4/3804e275",
"title": "SVM-Induced Dimensionality Reduction and Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2009/3804e275/12OmNzG4gwg",
"parentPublication": {
"id": "proceedings/icicta/2009/3804/4",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2011/02/ttp2011020338",
"title": "Learning Linear Discriminant Projections for Dimensionality Reduction of Image Descriptors",
"doi": null,
"abstractUrl": "/journal/tp/2011/02/ttp2011020338/13rRUwInvKC",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2011/04/ttp2011040657",
"title": "Central Subspace Dimensionality Reduction Using Covariance Operators",
"doi": null,
"abstractUrl": "/journal/tp/2011/04/ttp2011040657/13rRUwbJD63",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2008/03/ttp2008030535",
"title": "Dimensionality Reduction of Clustered Data Sets",
"doi": null,
"abstractUrl": "/journal/tp/2008/03/ttp2008030535/13rRUx0geqZ",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2000/06/i0623",
"title": "Fractional-Step Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tp/2000/06/i0623/13rRUxNmPET",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08546290",
"title": "Linear Discriminative Sparsity Preserving Projections for Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08546290/17D45WGGoLZ",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": null,
"article": {
"id": "12OmNBDyA6d",
"doi": "10.1109/ICICTA.2011.37",
"title": "Face Recognition by LLE Dimensionality Reduction",
"normalizedTitle": "Face Recognition by LLE Dimensionality Reduction",
"abstract": "Nowadays we are surrounded by colorful images and image processing has become an important subject. We have to carry on all kinds of implementations such as image classification, image recognition, image searching and so on. However, direct operation to those images is difficult because of the features -- nonlinear, high dimensionality, large quantity. To reduce the dimensionality and remain original features, people created many algorithms such as PCA, MCS and ANN. In this paper, I introduce one dimensionality reduction called locally linear embedding (LLE), which is created by Sam and Lawrence. The LLE algorithm is one nonlinear dimensionality reduction method. I make use of the LLE algorithm to do an experiment of face recognition. By the LLE algorithm I reduce the 92*112-dimension-image to 6 dimensions and successful recognize the face image.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Nowadays we are surrounded by colorful images and image processing has become an important subject. We have to carry on all kinds of implementations such as image classification, image recognition, image searching and so on. However, direct operation to those images is difficult because of the features -- nonlinear, high dimensionality, large quantity. To reduce the dimensionality and remain original features, people created many algorithms such as PCA, MCS and ANN. In this paper, I introduce one dimensionality reduction called locally linear embedding (LLE), which is created by Sam and Lawrence. The LLE algorithm is one nonlinear dimensionality reduction method. I make use of the LLE algorithm to do an experiment of face recognition. By the LLE algorithm I reduce the 92*112-dimension-image to 6 dimensions and successful recognize the face image.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Nowadays we are surrounded by colorful images and image processing has become an important subject. We have to carry on all kinds of implementations such as image classification, image recognition, image searching and so on. However, direct operation to those images is difficult because of the features -- nonlinear, high dimensionality, large quantity. To reduce the dimensionality and remain original features, people created many algorithms such as PCA, MCS and ANN. In this paper, I introduce one dimensionality reduction called locally linear embedding (LLE), which is created by Sam and Lawrence. The LLE algorithm is one nonlinear dimensionality reduction method. I make use of the LLE algorithm to do an experiment of face recognition. By the LLE algorithm I reduce the 92*112-dimension-image to 6 dimensions and successful recognize the face image.",
"fno": "05750570",
"keywords": [
"Face Recognition",
"Image Colour Analysis",
"Face Recognition",
"LLE Dimensionality Reduction",
"Image Processing",
"Locally Linear Embedding",
"Image Recognition",
"Image Searching",
"Image Classification",
"Image Recognition",
"Face Recognition",
"Cost Function",
"Principal Component Analysis",
"Image Reconstruction",
"Covariance Matrix",
"Vectors",
"Image Processing",
"Dimensionality Reduction",
"LLE",
"Face Recognition"
],
"authors": [
{
"affiliation": null,
"fullName": "Zhao Shenglin",
"givenName": "Zhao",
"surname": "Shenglin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Zhu Shan-an",
"givenName": "Zhu",
"surname": "Shan-an",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icicta",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2011-03-01T00:00:00",
"pubType": "proceedings",
"pages": "121-123",
"year": "2011",
"issn": null,
"isbn": "978-1-61284-289-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05750569",
"articleId": "12OmNBSSVj8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05750571",
"articleId": "12OmNzUPpdS",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sectech/2014/7775/0/07023278",
"title": "An Empirical Study of Dimensionality Reduction Methods for Biometric Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sectech/2014/07023278/12OmNAJDByq",
"parentPublication": {
"id": "proceedings/sectech/2014/7775/0",
"title": "2014 7th International Conference on Security Technology (SecTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2013/4999/0/06628827",
"title": "An Empirical Evaluation of Supervised Dimensionality Reduction for Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2013/06628827/12OmNApu5Ku",
"parentPublication": {
"id": "proceedings/icdar/2013/4999/0",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761861",
"title": "Ear recognition using LLE and IDLLE algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761861/12OmNC1oT2U",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icece/2010/4031/0/4031b605",
"title": "Research of Face Recognition Based on LLE and RBF Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/icece/2010/4031b605/12OmNvrdI2W",
"parentPublication": {
"id": "proceedings/icece/2010/4031/0",
"title": "Electrical and Control Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/grc/2010/7964/0/05576004",
"title": "Efficient Parallel Algorithm for Nonlinear Dimensionality Reduction on GPU",
"doi": null,
"abstractUrl": "/proceedings-article/grc/2010/05576004/12OmNwBT1o9",
"parentPublication": {
"id": "proceedings/grc/2010/7964/0",
"title": "2010 IEEE International Conference on Granular Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccee/2009/3925/2/3925b109",
"title": "Research of Face Recognition Based on Locally Linear Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/iccee/2009/3925b109/12OmNxEjY4k",
"parentPublication": {
"id": "proceedings/iccee/2009/3925/2",
"title": "Computer and Electrical Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761800",
"title": "An empirical study of facial components classification by integrating dimensionality reduction and clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761800/12OmNxFaLER",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscid/2008/3311/2/3311b102",
"title": "Application of Dimensionality Reduction Analysis to Fingerprint Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/iscid/2008/3311b102/12OmNxWuig7",
"parentPublication": {
"id": "proceedings/iscid/2008/3311/2",
"title": "2008 International Symposium on Computational Intelligence and Design",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2007/1016/0/04285062",
"title": "Dimensionality Reduction with Adaptive Approximation",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04285062/12OmNzFdt4Z",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2019/5686/0/568600a577",
"title": "Autoencoder Based Dimensionality Reduction of Feature Vectors for Object Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2019/568600a577/1j9xB188lAk",
"parentPublication": {
"id": "proceedings/sitis/2019/5686/0",
"title": "2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNx5GU2w",
"title": "2013 IEEE International Conference on High Performance Computing and Communications (HPCC) & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (EUC)",
"acronym": "hpcc-euc",
"groupId": "1002461",
"volume": "0",
"displayVolume": "0",
"year": "2013",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzFMFpX",
"doi": "10.1109/HPCC.and.EUC.2013.57",
"title": "A Robust Dimensionality Reduction Method from Laplacian Orientations",
"normalizedTitle": "A Robust Dimensionality Reduction Method from Laplacian Orientations",
"abstract": "Most dimensionality reduction methods are usually based on dissimilarity measurement of pixel intensities which can not obtain a more robust dissimilarity measurement. To address this problem, in this paper, we propose a novel robust dimensionality reduction method from Laplacian orientations. This method does not directly manipulate pixel intensity, which introduces Laplacian orientations, combined with the kernel method, and ultimately robust dimensionality reduction. The use of the Laplacian orientations results in a more robust dissimilarity measurement between images. Our method is as simple as standard intensity-based learning, yet much more powerful for efficient dimensionality reduction method. Our experiments show that the proposed method for different expressions, different illumination conditions and different occlusions under different illumination conditions has better robustness, and achieves a higher recognition rate. For a single sample per person, the proposed algorithm can also obtain a higher recognition rate.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Most dimensionality reduction methods are usually based on dissimilarity measurement of pixel intensities which can not obtain a more robust dissimilarity measurement. To address this problem, in this paper, we propose a novel robust dimensionality reduction method from Laplacian orientations. This method does not directly manipulate pixel intensity, which introduces Laplacian orientations, combined with the kernel method, and ultimately robust dimensionality reduction. The use of the Laplacian orientations results in a more robust dissimilarity measurement between images. Our method is as simple as standard intensity-based learning, yet much more powerful for efficient dimensionality reduction method. Our experiments show that the proposed method for different expressions, different illumination conditions and different occlusions under different illumination conditions has better robustness, and achieves a higher recognition rate. For a single sample per person, the proposed algorithm can also obtain a higher recognition rate.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Most dimensionality reduction methods are usually based on dissimilarity measurement of pixel intensities which can not obtain a more robust dissimilarity measurement. To address this problem, in this paper, we propose a novel robust dimensionality reduction method from Laplacian orientations. This method does not directly manipulate pixel intensity, which introduces Laplacian orientations, combined with the kernel method, and ultimately robust dimensionality reduction. The use of the Laplacian orientations results in a more robust dissimilarity measurement between images. Our method is as simple as standard intensity-based learning, yet much more powerful for efficient dimensionality reduction method. Our experiments show that the proposed method for different expressions, different illumination conditions and different occlusions under different illumination conditions has better robustness, and achieves a higher recognition rate. For a single sample per person, the proposed algorithm can also obtain a higher recognition rate.",
"fno": "06831939",
"keywords": [
"Laplace Equations",
"Kernel",
"Principal Component Analysis",
"Robustness",
"Lighting",
"Databases",
"Face Recognition",
"Laplacian Orientations",
"Dimensionality Reduction",
"Kernel Principal Component Analysis"
],
"authors": [
{
"affiliation": null,
"fullName": "Zhaokui Li",
"givenName": "Zhaokui",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Lixin Ding",
"givenName": "Lixin",
"surname": "Ding",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Yan Wang",
"givenName": "Yan",
"surname": "Wang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "hpcc-euc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2013-11-01T00:00:00",
"pubType": "proceedings",
"pages": "345-351",
"year": "2013",
"issn": null,
"isbn": "978-0-7695-5088-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06831938",
"articleId": "12OmNrH1PBW",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06831940",
"articleId": "12OmNBlFQZy",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sectech/2014/7775/0/07023278",
"title": "An Empirical Study of Dimensionality Reduction Methods for Biometric Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sectech/2014/07023278/12OmNAJDByq",
"parentPublication": {
"id": "proceedings/sectech/2014/7775/0",
"title": "2014 7th International Conference on Security Technology (SecTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2011/289/1/05750570",
"title": "Face Recognition by LLE Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2011/05750570/12OmNBDyA6d",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761254",
"title": "Local Regularized Least-Square Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761254/12OmNviZlgj",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csie/2009/3507/6/3507f043",
"title": "Laplacian MinMax Discriminant Projections",
"doi": null,
"abstractUrl": "/proceedings-article/csie/2009/3507f043/12OmNxjjEe3",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209b609",
"title": "Laplacian Support Vector Analysis for Subspace Discriminative Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209b609/12OmNyywxFA",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2007/1016/0/04285062",
"title": "Dimensionality Reduction with Adaptive Approximation",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04285062/12OmNzFdt4Z",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/passat-socialcom/2012/5638/0/06406304",
"title": "Dimensionality Reduction for Emotional Speech Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/passat-socialcom/2012/06406304/12OmNzSQdrs",
"parentPublication": {
"id": "proceedings/passat-socialcom/2012/5638/0",
"title": "2012 International Conference on Privacy, Security, Risk and Trust (PASSAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2012/12/ttp2012122454",
"title": "Subspace Learning from Image Gradient Orientations",
"doi": null,
"abstractUrl": "/journal/tp/2012/12/ttp2012122454/13rRUB6Sq1D",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2007/01/04016549",
"title": "Graph Embedding and Extensions: A General Framework for Dimensionality Reduction",
"doi": null,
"abstractUrl": "/journal/tp/2007/01/04016549/13rRUxEhFtN",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2016/03/07172559",
"title": "Laplacian Regularized Low-Rank Representation and Its Applications",
"doi": null,
"abstractUrl": "/journal/tp/2016/03/07172559/13rRUyv53GC",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBhpS6P",
"title": "2012 International Conference on Privacy, Security, Risk and Trust (PASSAT)",
"acronym": "passat-socialcom",
"groupId": "1800612",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzSQdrs",
"doi": "10.1109/SocialCom-PASSAT.2012.83",
"title": "Dimensionality Reduction for Emotional Speech Recognition",
"normalizedTitle": "Dimensionality Reduction for Emotional Speech Recognition",
"abstract": "The number of speech features that are introduced to emotional speech recognition exceeds some thousands and this makes dimensionality reduction an inevitable part of an emotional speech recognition system. The elastic net, the greedy feature selection, and the supervised principal component analysis are three recently developed dimensionality reduction algorithms that we have considered their application to tackle this issue. Together with PCA, these four methods include both supervised and unsupervised, as well as filter and projection-type dimensionality reduction methods. For experimental reasons, we have chosen VAM corpus. We have extracted two sets of features and have investigated the efficiency of the application of the four dimensionality reduction methods to the combination of the two sets, besides each of the two. The experimental results of this study show that in spite of a dimensionality reduction stage, a longer vector of speech features does not necessarily result in a more accurate prediction of emotion.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The number of speech features that are introduced to emotional speech recognition exceeds some thousands and this makes dimensionality reduction an inevitable part of an emotional speech recognition system. The elastic net, the greedy feature selection, and the supervised principal component analysis are three recently developed dimensionality reduction algorithms that we have considered their application to tackle this issue. Together with PCA, these four methods include both supervised and unsupervised, as well as filter and projection-type dimensionality reduction methods. For experimental reasons, we have chosen VAM corpus. We have extracted two sets of features and have investigated the efficiency of the application of the four dimensionality reduction methods to the combination of the two sets, besides each of the two. The experimental results of this study show that in spite of a dimensionality reduction stage, a longer vector of speech features does not necessarily result in a more accurate prediction of emotion.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The number of speech features that are introduced to emotional speech recognition exceeds some thousands and this makes dimensionality reduction an inevitable part of an emotional speech recognition system. The elastic net, the greedy feature selection, and the supervised principal component analysis are three recently developed dimensionality reduction algorithms that we have considered their application to tackle this issue. Together with PCA, these four methods include both supervised and unsupervised, as well as filter and projection-type dimensionality reduction methods. For experimental reasons, we have chosen VAM corpus. We have extracted two sets of features and have investigated the efficiency of the application of the four dimensionality reduction methods to the combination of the two sets, besides each of the two. The experimental results of this study show that in spite of a dimensionality reduction stage, a longer vector of speech features does not necessarily result in a more accurate prediction of emotion.",
"fno": "06406304",
"keywords": [
"Data Reduction",
"Emotion Recognition",
"Feature Extraction",
"Greedy Algorithms",
"Principal Component Analysis",
"Speech Recognition",
"Speech Features",
"Emotional Speech Recognition System",
"Greedy Feature Selection",
"Elastic Net",
"Supervised Principal Component Analysis",
"PCA",
"Projection Type Dimensionality Reduction Methods",
"Filter Type Dimensionality Reduction Methods",
"VAM Corpus",
"Dimensionality Reduction Stage",
"Principal Component Analysis",
"Accuracy",
"Speech",
"Feature Extraction",
"Speech Recognition",
"Databases",
"Vectors",
"Emotional Speech Recognition",
"Dimensionality Reduction"
],
"authors": [
{
"affiliation": null,
"fullName": "Pouria Fewzee",
"givenName": "Pouria",
"surname": "Fewzee",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Fakhri Karray",
"givenName": "Fakhri",
"surname": "Karray",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "passat-socialcom",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-09-01T00:00:00",
"pubType": "proceedings",
"pages": "532-537",
"year": "2012",
"issn": null,
"isbn": "978-1-4673-5638-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06406303",
"articleId": "12OmNwp74yH",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06406305",
"articleId": "12OmNwwuE3Z",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sectech/2014/7775/0/07023278",
"title": "An Empirical Study of Dimensionality Reduction Methods for Biometric Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sectech/2014/07023278/12OmNAJDByq",
"parentPublication": {
"id": "proceedings/sectech/2014/7775/0",
"title": "2014 7th International Conference on Security Technology (SecTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2013/4999/0/06628827",
"title": "An Empirical Evaluation of Supervised Dimensionality Reduction for Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2013/06628827/12OmNApu5Ku",
"parentPublication": {
"id": "proceedings/icdar/2013/4999/0",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2011/289/1/05750570",
"title": "Face Recognition by LLE Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2011/05750570/12OmNBDyA6d",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icassp/2004/8484/1/01326055",
"title": "Automatic emotional speech classification",
"doi": null,
"abstractUrl": "/proceedings-article/icassp/2004/01326055/12OmNBv2Ci8",
"parentPublication": {
"id": "proceedings/icassp/2004/8484/1",
"title": "2004 IEEE International Conference on Acoustics, Speech, and Signal Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icccnt/2012/9999/0/06395989",
"title": "Principal factor analysis and SVM based effective speaker recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icccnt/2012/06395989/12OmNy4IF08",
"parentPublication": {
"id": "proceedings/icccnt/2012/9999/0",
"title": "2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2012/2216/0/06460366",
"title": "Graph-based dimensionality reduction for KNN-based image annotation",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460366/12OmNzTppIy",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcs/1999/0253/1/02539840",
"title": "Emotion Recognition and Synthesis System on Speech",
"doi": null,
"abstractUrl": "/proceedings-article/icmcs/1999/02539840/12OmNzvQI6T",
"parentPublication": {
"id": "proceedings/icmcs/1999/0253/1",
"title": "Multimedia Computing and Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/2013/01/tta2013010047",
"title": "Classifier-based learning of nonlinear feature manifold for visualization of emotional speech prosody",
"doi": null,
"abstractUrl": "/journal/ta/2013/01/tta2013010047/13rRUxYrbKn",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2019/5686/0/568600a577",
"title": "Autoencoder Based Dimensionality Reduction of Feature Vectors for Object Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2019/568600a577/1j9xB188lAk",
"parentPublication": {
"id": "proceedings/sitis/2019/5686/0",
"title": "2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09543512",
"title": "Unsupervised Dimensionality Reduction Based on Fusing Multiple Clustering Results",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09543512/1x4UGJ56Qpy",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNCbU3aO",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"acronym": "icdar",
"groupId": "1000219",
"volume": "0",
"displayVolume": "0",
"year": "2013",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNApLGu7",
"doi": "10.1109/ICDAR.2013.68",
"title": "WebGT: An Interactive Web-Based System for Historical Document Ground Truth Generation",
"normalizedTitle": "WebGT: An Interactive Web-Based System for Historical Document Ground Truth Generation",
"abstract": "We present WebGT, the first web-based system to help users produce ground truth data for document images. This user-friendly software system helps historians and computer scientists collectively annotate historical documents. It supports real time collaboration among remote sites independent of the local operating system and also provides several novel semi-automatic tools that have proven effective for annotating degraded documents.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present WebGT, the first web-based system to help users produce ground truth data for document images. This user-friendly software system helps historians and computer scientists collectively annotate historical documents. It supports real time collaboration among remote sites independent of the local operating system and also provides several novel semi-automatic tools that have proven effective for annotating degraded documents.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present WebGT, the first web-based system to help users produce ground truth data for document images. This user-friendly software system helps historians and computer scientists collectively annotate historical documents. It supports real time collaboration among remote sites independent of the local operating system and also provides several novel semi-automatic tools that have proven effective for annotating degraded documents.",
"fno": "06628633",
"keywords": [
"Text Analysis",
"Layout",
"Educational Institutions",
"Computers",
"Collaboration",
"Operating Systems",
"Robustness",
"On Line",
"Annotation",
"Transcription",
"Ground Truth",
"Web System"
],
"authors": [
{
"affiliation": null,
"fullName": "Ofer Biller",
"givenName": "Ofer",
"surname": "Biller",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Abedelkadir Asi",
"givenName": "Abedelkadir",
"surname": "Asi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Klara Kedem",
"givenName": "Klara",
"surname": "Kedem",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Itshak Dinstein",
"givenName": "Itshak",
"surname": "Dinstein",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdar",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2013-08-01T00:00:00",
"pubType": "proceedings",
"pages": "305-308",
"year": "2013",
"issn": "1520-5363",
"isbn": "978-0-7695-4999-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06628632",
"articleId": "12OmNzl3WVd",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06628634",
"articleId": "12OmNyen1m7",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2009/3725/0/3725b275",
"title": "Automated Ground Truth Data Generation for Newspaper Document Images",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2009/3725b275/12OmNCd2rqL",
"parentPublication": {
"id": "proceedings/icdar/2009/3725/0",
"title": "2009 10th International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icfhr/2014/4335/0/06981001",
"title": "Hybrid Feature Selection for Historical Document Layout Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icfhr/2014/06981001/12OmNxwENzF",
"parentPublication": {
"id": "proceedings/icfhr/2014/4335/0",
"title": "2014 14th International Conference on Frontiers in Handwriting Recognition (ICFHR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/das/2014/3244/0/3244a247",
"title": "Ground-Truth and Performance Evaluation for Page Layout Analysis of Born-Digital Documents",
"doi": null,
"abstractUrl": "/proceedings-article/das/2014/3244a247/12OmNy2JtaM",
"parentPublication": {
"id": "proceedings/das/2014/3244/0",
"title": "2014 11th IAPR International Workshop on Document Analysis Systems (DAS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2015/9721/0/9721a649",
"title": "A Framework for Compilation of Multi-lingual Handwritten Database: Four Levels XML Ground-Truth",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2015/9721a649/12OmNz5JCfV",
"parentPublication": {
"id": "proceedings/sitis/2015/9721/0",
"title": "2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2010/4109/0/4109a245",
"title": "Document Segmentation Using Pixel-Accurate Ground Truth",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2010/4109a245/12OmNzEmFFv",
"parentPublication": {
"id": "proceedings/icpr/2010/4109/0",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/das/2016/1792/0/1792a126",
"title": "Creating Ground Truth for Historical Manuscripts with Document Graphs and Scribbling Interaction",
"doi": null,
"abstractUrl": "/proceedings-article/das/2016/1792a126/12OmNzUPplv",
"parentPublication": {
"id": "proceedings/das/2016/1792/0",
"title": "2016 12th IAPR Workshop on Document Analysis Systems (DAS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2015/1805/0/07333851",
"title": "Automatic and interactive rule inference without ground truth",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2015/07333851/12OmNzdoMMm",
"parentPublication": {
"id": "proceedings/icdar/2015/1805/0",
"title": "2015 13th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2011/4520/0/4520b516",
"title": "Historical Document Layout Analysis Competition",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2011/4520b516/12OmNzl3X1r",
"parentPublication": {
"id": "proceedings/icdar/2011/4520/0",
"title": "2011 International Conference on Document Analysis and Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icfhr/2020/9966/0/996600a031",
"title": "Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization",
"doi": null,
"abstractUrl": "/proceedings-article/icfhr/2020/996600a031/1p2VuMaLbnq",
"parentPublication": {
"id": "proceedings/icfhr/2020/9966/0",
"title": "2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icfhr/2020/9966/0/996600a091",
"title": "docExtractor: An off-the-shelf historical document element extraction",
"doi": null,
"abstractUrl": "/proceedings-article/icfhr/2020/996600a091/1p2VvK2HDl6",
"parentPublication": {
"id": "proceedings/icfhr/2020/9966/0",
"title": "2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNqBtiPK",
"title": "2014 IEEE 10th International Conference on e-Science (e-Science)",
"acronym": "e-science",
"groupId": "1001511",
"volume": "2",
"displayVolume": "2",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyrIaJC",
"doi": "10.1109/eScience.2014.50",
"title": "Exploratory Information Extraction from a Historical Dictionary",
"normalizedTitle": "Exploratory Information Extraction from a Historical Dictionary",
"abstract": "We describe a preliminary project of extracting information from an extant dictionary of historical biographies, the \"Dicionário Histórico-Biográfico Brasileiro\" (the Brazilian Historical and Biographical Dictionary, shortened as DHBB), a longstanding project at the 'Centro de Pesquisa e Documentação de História Contemporânea do Brasil' (CPDOC) of the Fundação Getulio Vargas (FGV). For information extraction, we rely on Natural Language Processing tools such as FreeLing as well as our resources NomLex-PT, a lexicon of nominalizations, and OpenWN-PT, a Portuguese version of Princeton's WordNet database. While our project currently highlights the potential of information extraction in a fun exploratory manner, we also discuss the engaging of historians interested in the affordances of digital tools.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We describe a preliminary project of extracting information from an extant dictionary of historical biographies, the \"Dicionário Histórico-Biográfico Brasileiro\" (the Brazilian Historical and Biographical Dictionary, shortened as DHBB), a longstanding project at the 'Centro de Pesquisa e Documentação de História Contemporânea do Brasil' (CPDOC) of the Fundação Getulio Vargas (FGV). For information extraction, we rely on Natural Language Processing tools such as FreeLing as well as our resources NomLex-PT, a lexicon of nominalizations, and OpenWN-PT, a Portuguese version of Princeton's WordNet database. While our project currently highlights the potential of information extraction in a fun exploratory manner, we also discuss the engaging of historians interested in the affordances of digital tools.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We describe a preliminary project of extracting information from an extant dictionary of historical biographies, the \"Dicionário Histórico-Biográfico Brasileiro\" (the Brazilian Historical and Biographical Dictionary, shortened as DHBB), a longstanding project at the 'Centro de Pesquisa e Documentação de História Contemporânea do Brasil' (CPDOC) of the Fundação Getulio Vargas (FGV). For information extraction, we rely on Natural Language Processing tools such as FreeLing as well as our resources NomLex-PT, a lexicon of nominalizations, and OpenWN-PT, a Portuguese version of Princeton's WordNet database. While our project currently highlights the potential of information extraction in a fun exploratory manner, we also discuss the engaging of historians interested in the affordances of digital tools.",
"fno": "06972090",
"keywords": [
"Biographies",
"Dictionaries",
"History",
"Natural Language Processing",
"Exploratory Information Extraction",
"Historical Dictionary",
"Historical Biographies",
"Diciona X 0301 Rio Histo X 0301 Rico Biogra X 0301 Fico Brasileiro",
"Brazilian Historical And Biographical Dictionary",
"DHBB",
"Natural Language Processing Tools",
"Free Ling",
"Nom Lex PT",
"Open WN PT",
"Princeton Word Net Database",
"Digital Tools",
"Dictionaries",
"History",
"Organizations",
"Biographies",
"Semantics",
"Cities And Towns",
"Biographical Dictionary",
"Information Extraction",
"Nlp",
"Wordnet",
"Nomlex",
"Nominalization"
],
"authors": [
{
"affiliation": "Nuance Commun., USA",
"fullName": "Valeria De Paiva",
"givenName": "Valeria",
"surname": "De Paiva",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "FGV/CPDOC, Brazil",
"fullName": "Dario Augusto Borges Oliveira",
"givenName": "Dario Augusto Borges",
"surname": "Oliveira",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "FGV/CPDOC, Brazil",
"fullName": "Suemi Higuchi",
"givenName": "Suemi",
"surname": "Higuchi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "FGV/EMAp, IBM Res., São Paulo, Brazil",
"fullName": "Alexandre Rademaker",
"givenName": "Alexandre",
"surname": "Rademaker",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tsinghua Univ., Beijing, China",
"fullName": "Gerard De Melo",
"givenName": "Gerard",
"surname": "De Melo",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "e-science",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-10-01T00:00:00",
"pubType": "proceedings",
"pages": "11-18",
"year": "2014",
"issn": null,
"isbn": "978-1-4799-4288-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06972089",
"articleId": "12OmNwDj1cC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06972091",
"articleId": "12OmNrYlmO1",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/big-data/2014/5666/0/07004244",
"title": "TRISTAN: Real-time analytics on massive time series using sparse dictionary compression",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2014/07004244/12OmNBDQblI",
"parentPublication": {
"id": "proceedings/big-data/2014/5666/0",
"title": "2014 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asap/2013/0494/0/06567551",
"title": "A high-speed and large-scale dictionary matching engine for Information Extraction systems",
"doi": null,
"abstractUrl": "/proceedings-article/asap/2013/06567551/12OmNCm7BE1",
"parentPublication": {
"id": "proceedings/asap/2013/0494/0",
"title": "2013 IEEE 24th International Conference on Application-Specific Systems, Architectures and Processors",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/caia/1993/3840/0/00366656",
"title": "Automated dictionary construction for information extraction from text",
"doi": null,
"abstractUrl": "/proceedings-article/caia/1993/00366656/12OmNrYCXQ3",
"parentPublication": {
"id": "proceedings/caia/1993/3840/0",
"title": "Proceedings of 9th IEEE Conference on Artificial Intelligence for Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/date/2008/3/0/04484882",
"title": "A Same/Different Fault Dictionary: An Extended Pass/Fail Fault Dictionary with Improved Diagnostic Resolution",
"doi": null,
"abstractUrl": "/proceedings-article/date/2008/04484882/12OmNweTvMe",
"parentPublication": {
"id": "proceedings/date/2008/3/0",
"title": "Design, Automation & Test in Europe. DATE'08",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/1994/6270/2/00576918",
"title": "Using a partitioned dictionary for contextual post-processing of OCR-results",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1994/00576918/12OmNwsNRcP",
"parentPublication": {
"id": "proceedings/icpr/1994/6270/2",
"title": "Proceedings of 12th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2016/4320/0/07945797",
"title": "HAD, a platform to create a historical dictionary",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2016/07945797/12OmNxcdG2F",
"parentPublication": {
"id": "proceedings/aiccsa/2016/4320/0",
"title": "2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2014/11/06787085",
"title": "Information-Theoretic Dictionary Learning for Image Classification",
"doi": null,
"abstractUrl": "/journal/tp/2014/11/06787085/13rRUwbs2hC",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2018/9120/0/08612778",
"title": "Word Sense Disambiguation using Skip Gram Model to Create a Historical Dictionary for Arabic",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2018/08612778/17D45Vu1Tze",
"parentPublication": {
"id": "proceedings/aiccsa/2018/9120/0",
"title": "2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mark/1979/3181/0/08817065",
"title": "English dictionary searching with little extra space",
"doi": null,
"abstractUrl": "/proceedings-article/mark/1979/08817065/1cTIUu1a4ZG",
"parentPublication": {
"id": "proceedings/mark/1979/3181/0",
"title": "1979 International Workshop on Managing Requirements Knowledge",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/laclo/2018/0382/0/038200a341",
"title": "Dictionary in Libras to Disseminate Information on Human Sexuality An Application for Mobile Devices (DiSLibras)",
"doi": null,
"abstractUrl": "/proceedings-article/laclo/2018/038200a341/1cdOi0lFgxW",
"parentPublication": {
"id": "proceedings/laclo/2018/0382/0",
"title": "2018 XIII Latin American Conference on Learning Technologies (LACLO)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNylsZC5",
"title": "2018 IEEE International Conference on Healthcare Informatics (ICHI)",
"acronym": "ichi",
"groupId": "1803080",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNz6iOc1",
"doi": "10.1109/ICHI.2018.00011",
"title": "Process Mining the Trauma Resuscitation Patient Cohorts",
"normalizedTitle": "Process Mining the Trauma Resuscitation Patient Cohorts",
"abstract": "In this study, we present a framework for analyzing associations between patient cohorts and the trauma resuscitation procedures their patients received. Our framework works by quantifying associations between discovered patient cohorts and treatment patterns. We evaluated our framework on a trauma resuscitation dataset collected in a level 1 trauma center. Our experimental results show that using weights learned by our algorithm improves measurements of patient similarity. Four patient cohorts were then found via clustering, and statistically significant resuscitation patterns were discovered using process mining techniques. Though only tested on the trauma resuscitation process, our framework can be generalized to analyze other medical processes.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this study, we present a framework for analyzing associations between patient cohorts and the trauma resuscitation procedures their patients received. Our framework works by quantifying associations between discovered patient cohorts and treatment patterns. We evaluated our framework on a trauma resuscitation dataset collected in a level 1 trauma center. Our experimental results show that using weights learned by our algorithm improves measurements of patient similarity. Four patient cohorts were then found via clustering, and statistically significant resuscitation patterns were discovered using process mining techniques. Though only tested on the trauma resuscitation process, our framework can be generalized to analyze other medical processes.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this study, we present a framework for analyzing associations between patient cohorts and the trauma resuscitation procedures their patients received. Our framework works by quantifying associations between discovered patient cohorts and treatment patterns. We evaluated our framework on a trauma resuscitation dataset collected in a level 1 trauma center. Our experimental results show that using weights learned by our algorithm improves measurements of patient similarity. Four patient cohorts were then found via clustering, and statistically significant resuscitation patterns were discovered using process mining techniques. Though only tested on the trauma resuscitation process, our framework can be generalized to analyze other medical processes.",
"fno": "537701a029",
"keywords": [
"Data Mining",
"Injuries",
"Learning Artificial Intelligence",
"Medical Computing",
"Patient Treatment",
"Pattern Clustering",
"Treatment Patterns",
"Trauma Resuscitation Dataset",
"Level 1 Trauma Center",
"Patient Similarity",
"Statistically Significant Resuscitation Patterns",
"Process Mining Techniques",
"Trauma Resuscitation Process",
"Trauma Resuscitation Patient Cohorts",
"Trauma Resuscitation Procedures",
"Injuries",
"Clustering Algorithms",
"Weight Measurement",
"Data Mining",
"Correlation",
"Classification Algorithms",
"Analytical Models",
"Process Mining",
"Patient Cohort Analysis",
"Trauma Resuscitation",
"Medical Workflow Analysis"
],
"authors": [
{
"affiliation": null,
"fullName": "Sen Yang",
"givenName": "Sen",
"surname": "Yang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Fei Tao",
"givenName": "Fei",
"surname": "Tao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Jingyuan Li",
"givenName": "Jingyuan",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Dawei Wang",
"givenName": "Dawei",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Shuhong Chen",
"givenName": "Shuhong",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Omar Z. Ahmed",
"givenName": "Omar Z.",
"surname": "Ahmed",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Ivan Marsic",
"givenName": "Ivan",
"surname": "Marsic",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Randall S. Burd",
"givenName": "Randall S.",
"surname": "Burd",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ichi",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-06-01T00:00:00",
"pubType": "proceedings",
"pages": "29-35",
"year": "2018",
"issn": "2575-2634",
"isbn": "978-1-5386-5377-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "537701a022",
"articleId": "12OmNqOOrMj",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "537701a036",
"articleId": "12OmNxZ2Gmd",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/big-data/2015/9926/0/07364053",
"title": "Ensemble prediction of vascular injury in Trauma care: Initial efforts towards data-driven, low-cost screening",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2015/07364053/12OmNANkohg",
"parentPublication": {
"id": "proceedings/big-data/2015/9926/0",
"title": "2015 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2013/5545/0/06553758",
"title": "Video based activity recognition in trauma resuscitation",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2013/06553758/12OmNApLGKY",
"parentPublication": {
"id": "proceedings/fg/2013/5545/0",
"title": "2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2013/5089/0/5089a248",
"title": "Automated Trauma Incident Cubes Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2013/5089a248/12OmNwkhTdq",
"parentPublication": {
"id": "proceedings/ichi/2013/5089/0",
"title": "2013 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/2013/1053/0/06627766",
"title": "Remote supported trauma care: Understanding the situation from afar",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2013/06627766/12OmNxRnvWB",
"parentPublication": {
"id": "proceedings/cbms/2013/1053/0",
"title": "2013 IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2018/5377/0/537701a036",
"title": "Intention Mining in Medical Process: A Case Study in Trauma Resuscitation",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2018/537701a036/12OmNxZ2Gmd",
"parentPublication": {
"id": "proceedings/ichi/2018/5377/0",
"title": "2018 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2017/4881/0/4881a239",
"title": "Language-Based Process Phase Detection in the Trauma Resuscitation",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2017/4881a239/12OmNyXMQmy",
"parentPublication": {
"id": "proceedings/ichi/2017/4881/0",
"title": "2017 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2016/04/07111343",
"title": "Passive RFID for Object and Use Detection during Trauma Resuscitation",
"doi": null,
"abstractUrl": "/journal/tm/2016/04/07111343/13rRUxBa5sy",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/2019/2286/0/228600a237",
"title": "Pervasive Tracking for Time-Dependent Acute Patient Flow: A Case Study in Trauma Management",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2019/228600a237/1cdO14hL9iE",
"parentPublication": {
"id": "proceedings/cbms/2019/2286/0",
"title": "2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2020/5382/0/09374399",
"title": "Video-based Concurrent Activity Recognition for Trauma Resuscitation",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2020/09374399/1rUIZDMVwRi",
"parentPublication": {
"id": "proceedings/ichi/2020/5382/0",
"title": "2020 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2020/5382/0/09374372",
"title": "Speech-Based Activity Recognition for Trauma Resuscitation",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2020/09374372/1rUJ1Hkdjiw",
"parentPublication": {
"id": "proceedings/ichi/2020/5382/0",
"title": "2020 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzUPpw7",
"title": "2015 International Conference on Learning and Teaching in Computing and Engineering (LaTiCE)",
"acronym": "latice",
"groupId": "1802640",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzUxOcF",
"doi": "10.1109/LaTiCE.2015.30",
"title": "Teaching High School Computer Science with Videos of Historical Figures -- An Augmented Reality Approach",
"normalizedTitle": "Teaching High School Computer Science with Videos of Historical Figures -- An Augmented Reality Approach",
"abstract": "This study investigated the effects of teaching history of computing with videos of historical figures. Augmented reality (AR) techniques were applied to assist student accessing the videos of historical figures while reading a printed textbook. Whenever a student was interested in a historical figure, one could use a tablet PC to scan the figure's picture, and the corresponding video about the person would then be played on the screen. We adapted thirteen videos of historical figures in computer network field and adopted a quasi-experimental method to evaluate the effectiveness of the AR-based learning approach. Two classes of high school students, with a total of 84 students, participated in the experiment. One class of the students used Tablet PCs to access the videos of historical figures, and the other class using traditional didactic instruction served as the control group. The data collected for analysis are students' achievement test scores and answers to a questionnaire, which consists of questions on attitudes toward learning, perspectives of nature of science, and perceptions on the AR activities. Our findings showed that the AR-based historical figure videos helped students comprehend learning contents and promoted their attitudes toward learning. Students appreciated the convenience of using AR tools to access the history videos. Future research should investigate other approaches to integrate AR with the videos of historical figure, and in general, to integrate AR with other media format of computing history.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This study investigated the effects of teaching history of computing with videos of historical figures. Augmented reality (AR) techniques were applied to assist student accessing the videos of historical figures while reading a printed textbook. Whenever a student was interested in a historical figure, one could use a tablet PC to scan the figure's picture, and the corresponding video about the person would then be played on the screen. We adapted thirteen videos of historical figures in computer network field and adopted a quasi-experimental method to evaluate the effectiveness of the AR-based learning approach. Two classes of high school students, with a total of 84 students, participated in the experiment. One class of the students used Tablet PCs to access the videos of historical figures, and the other class using traditional didactic instruction served as the control group. The data collected for analysis are students' achievement test scores and answers to a questionnaire, which consists of questions on attitudes toward learning, perspectives of nature of science, and perceptions on the AR activities. Our findings showed that the AR-based historical figure videos helped students comprehend learning contents and promoted their attitudes toward learning. Students appreciated the convenience of using AR tools to access the history videos. Future research should investigate other approaches to integrate AR with the videos of historical figure, and in general, to integrate AR with other media format of computing history.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This study investigated the effects of teaching history of computing with videos of historical figures. Augmented reality (AR) techniques were applied to assist student accessing the videos of historical figures while reading a printed textbook. Whenever a student was interested in a historical figure, one could use a tablet PC to scan the figure's picture, and the corresponding video about the person would then be played on the screen. We adapted thirteen videos of historical figures in computer network field and adopted a quasi-experimental method to evaluate the effectiveness of the AR-based learning approach. Two classes of high school students, with a total of 84 students, participated in the experiment. One class of the students used Tablet PCs to access the videos of historical figures, and the other class using traditional didactic instruction served as the control group. The data collected for analysis are students' achievement test scores and answers to a questionnaire, which consists of questions on attitudes toward learning, perspectives of nature of science, and perceptions on the AR activities. Our findings showed that the AR-based historical figure videos helped students comprehend learning contents and promoted their attitudes toward learning. Students appreciated the convenience of using AR tools to access the history videos. Future research should investigate other approaches to integrate AR with the videos of historical figure, and in general, to integrate AR with other media format of computing history.",
"fno": "9967a022",
"keywords": [
"Videos",
"History",
"Education",
"Computers",
"Augmented Reality",
"Context",
"Computer Networks",
"Augmented Reality",
"History Of Computing",
"Videos",
"Historical Figures"
],
"authors": [
{
"affiliation": null,
"fullName": "Ching-Yin Hsu",
"givenName": "Ching-Yin",
"surname": "Hsu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Mei-Wen Chen",
"givenName": "Mei-Wen",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Cheng-Chih Wu",
"givenName": "Cheng-Chih",
"surname": "Wu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "latice",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-04-01T00:00:00",
"pubType": "proceedings",
"pages": "22-25",
"year": "2015",
"issn": null,
"isbn": "978-1-4799-9967-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "9967a017",
"articleId": "12OmNB7LvE4",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "9967a026",
"articleId": "12OmNBghttz",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icalt/2015/7334/0/7334a132",
"title": "Augmented Reality Laboratory for High School Electrochemistry Course",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2015/7334a132/12OmNqBbHAA",
"parentPublication": {
"id": "proceedings/icalt/2015/7334/0",
"title": "2015 IEEE 15th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2013/4892/0/4892a031",
"title": "Manipulating Virtual Objects with Your Hands: A Case Study on Applying Desktop Augmented Reality at the Primary School",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2013/4892a031/12OmNrMHOpd",
"parentPublication": {
"id": "proceedings/hicss/2013/4892/0",
"title": "2013 46th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/Ismar-mashd/2015/9628/0/9628a009",
"title": "CI-Spy: Designing A Mobile Augmented Reality System for Scaffolding Historical Inquiry Learning",
"doi": null,
"abstractUrl": "/proceedings-article/Ismar-mashd/2015/9628a009/12OmNvkYxa6",
"parentPublication": {
"id": "proceedings/Ismar-mashd/2015/9628/0",
"title": "2015 IEEE International Symposium on Mixed and Augmented Reality - Media, Art, Social Science, Humanities and Design (ISMAR-MASH'D)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismarw/2016/3740/0/07836489",
"title": "Riverwalk: Incorporating Historical Photographs in Public Outdoor Augmented Reality Experiences",
"doi": null,
"abstractUrl": "/proceedings-article/ismarw/2016/07836489/12OmNvqmUM8",
"parentPublication": {
"id": "proceedings/ismarw/2016/3740/0",
"title": "2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-amh/2010/9339/0/05643289",
"title": "Augmented Reality Window: Digital reconstruction of a historical and cultural site for smart phones",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-amh/2010/05643289/12OmNwc3wrt",
"parentPublication": {
"id": "proceedings/ismar-amh/2010/9339/0",
"title": "2010 IEEE International Symposium on Mixed and Augmented Reality - Arts, Media, and Humanities",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2014/3922/0/07044094",
"title": "Engaging computer engineering students with an augmented reality software for laboratory exercises",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2014/07044094/12OmNznkK2B",
"parentPublication": {
"id": "proceedings/fie/2014/3922/0",
"title": "2014 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798058",
"title": "An Educational Augmented Reality Application for Elementary School Students Focusing on the Human Skeletal System",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798058/1cJ1fFJvYBy",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2019/4765/0/476500a034",
"title": "AR Tips: Augmented First-Person View Task Instruction Videos",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a034/1gysm0mzZlK",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2019/4765/0",
"title": "2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2020/6090/0/09155919",
"title": "Effects of Augmented Reality Assisted Learning Materials on Students’ Learning Outcomes",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2020/09155919/1m1j7NOETSg",
"parentPublication": {
"id": "proceedings/icalt/2020/6090/0",
"title": "2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2020/8508/0/850800a498",
"title": "Enhancing First-Person View Task Instruction Videos with Augmented Reality Cues",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2020/850800a498/1pyswTqrkZ2",
"parentPublication": {
"id": "proceedings/ismar/2020/8508/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNCbU3aO",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"acronym": "icdar",
"groupId": "1000219",
"volume": "0",
"displayVolume": "0",
"year": "2013",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzl3WVd",
"doi": "10.1109/ICDAR.2013.67",
"title": "Interactive Knowledge Learning for Ancient Images",
"normalizedTitle": "Interactive Knowledge Learning for Ancient Images",
"abstract": "This paper deals with cultural heritage preservation and ancient document indexing. In the management of historical documents, ancient images are described using semantic information, often manually annotated by historians. In this paper, we propose an approach to interactively propagate the historians' knowledge to a database of drop caps images manually populated by historians with drop caps image annotations. Based on a novel document indexing processing scheme which combines the use of the Zipf law and the use of bag of patterns, our approach extends the Bag of Words model to represent the knowledge by visual features through relevance feedback. Then annotation propagation is automatically performed to propagate knowledge to the drop caps image database. In this article, our approach is presented together with preliminary experimental results and an illustrative example.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper deals with cultural heritage preservation and ancient document indexing. In the management of historical documents, ancient images are described using semantic information, often manually annotated by historians. In this paper, we propose an approach to interactively propagate the historians' knowledge to a database of drop caps images manually populated by historians with drop caps image annotations. Based on a novel document indexing processing scheme which combines the use of the Zipf law and the use of bag of patterns, our approach extends the Bag of Words model to represent the knowledge by visual features through relevance feedback. Then annotation propagation is automatically performed to propagate knowledge to the drop caps image database. In this article, our approach is presented together with preliminary experimental results and an illustrative example.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper deals with cultural heritage preservation and ancient document indexing. In the management of historical documents, ancient images are described using semantic information, often manually annotated by historians. In this paper, we propose an approach to interactively propagate the historians' knowledge to a database of drop caps images manually populated by historians with drop caps image annotations. Based on a novel document indexing processing scheme which combines the use of the Zipf law and the use of bag of patterns, our approach extends the Bag of Words model to represent the knowledge by visual features through relevance feedback. Then annotation propagation is automatically performed to propagate knowledge to the drop caps image database. In this article, our approach is presented together with preliminary experimental results and an illustrative example.",
"fno": "06628632",
"keywords": [
"Visualization",
"Indexing",
"Semantics",
"Libraries",
"Image Color Analysis",
"Analytical Models",
"Relevance Feedback",
"Ancient Document Indexing",
"Bag Of Patterns",
"Key Word Visual Representation",
"Interactive Learning"
],
"authors": [
{
"affiliation": null,
"fullName": "Nhu-Van Nguyen",
"givenName": "Nhu-Van",
"surname": "Nguyen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Mickael Coustaty",
"givenName": "Mickael",
"surname": "Coustaty",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Alain Boucher",
"givenName": "Alain",
"surname": "Boucher",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Jean-Marc Ogier",
"givenName": "Jean-Marc",
"surname": "Ogier",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdar",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2013-08-01T00:00:00",
"pubType": "proceedings",
"pages": "300-304",
"year": "2013",
"issn": "1520-5363",
"isbn": "978-0-7695-4999-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06628631",
"articleId": "12OmNwqx4a2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06628633",
"articleId": "12OmNApLGu7",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/sitis/2016/5698/0/07907497",
"title": "Semantic and Visual Cues for Humanitarian Computing of Natural Disaster Damage Images",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2016/07907497/12OmNBpmDPI",
"parentPublication": {
"id": "proceedings/sitis/2016/5698/0",
"title": "2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2015/7644/0/7644a265",
"title": "Cartoon Material Annotation and Retrieval System for Web-Interactive-Service Cartoon Making",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2015/7644a265/12OmNCdk2wA",
"parentPublication": {
"id": "proceedings/icicta/2015/7644/0",
"title": "2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iset/2017/3031/0/08005422",
"title": "Interactive Learning Resources Based on Cognitive Load: Design and Application",
"doi": null,
"abstractUrl": "/proceedings-article/iset/2017/08005422/12OmNqJHFJC",
"parentPublication": {
"id": "proceedings/iset/2017/3031/0",
"title": "2017 International Symposium on Educational Technology (ISET)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsc/2016/0662/0/0662a400",
"title": "Learning Commonsense Knowledge Models for Semantic Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/icsc/2016/0662a400/12OmNwDj136",
"parentPublication": {
"id": "proceedings/icsc/2016/0662/0",
"title": "2016 IEEE Tenth International Conference on Semantic Computing (ICSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2012/2216/0/06460735",
"title": "Visual saliency and categorisation of abstract images",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460735/12OmNxjjEfM",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2003/05/k1338",
"title": "Using Hybrid Knowledge Engineering and Image Processing in Color Virtual Restoration of Ancient Murals",
"doi": null,
"abstractUrl": "/journal/tk/2003/05/k1338/13rRUILtJrh",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mipr/2019/1198/0/119800a085",
"title": "Machine Learning on Biomedical Images: Interactive Learning, Transfer Learning, Class Imbalance, and Beyond",
"doi": null,
"abstractUrl": "/proceedings-article/mipr/2019/119800a085/19wB4ENUNe8",
"parentPublication": {
"id": "proceedings/mipr/2019/1198/0",
"title": "2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200m2127",
"title": "Learning Attribute-driven Disentangled Representations for Interactive Fashion Retrieval",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200m2127/1BmKKdEwsda",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2021/3864/0/09428440",
"title": "Learning Multiple Semantic Knowledge For Cross-Domain Unsupervised Vehicle Re-Identification",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2021/09428440/1uim7V62jYY",
"parentPublication": {
"id": "proceedings/icme/2021/3864/0",
"title": "2021 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/escience/2021/0361/0/036100a128",
"title": "Exploring Learning Approaches for Ancient Greek Character Recognition with Citizen Science Data",
"doi": null,
"abstractUrl": "/proceedings-article/escience/2021/036100a128/1y14ByRQIDK",
"parentPublication": {
"id": "proceedings/escience/2021/0361/0",
"title": "2021 IEEE 17th International Conference on eScience (eScience)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J2XGOP3M1G",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"acronym": "vis4dh",
"groupId": "1839705",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J2XGWp7vqw",
"doi": "10.1109/VIS4DH57440.2022.00012",
"title": "From Historical Documents To Social Network Visualization: Potential Pitfalls and Network Modeling",
"normalizedTitle": "From Historical Documents To Social Network Visualization: Potential Pitfalls and Network Modeling",
"abstract": "We describe the workflow followed by historians when conducting a Historical Social Network Analysis (HSNA) with five steps: textual sources acquisition, digitization, annotation, network creation, and analysis/visualization. While most analysis and visualization tools only support the last step, we argue that addressing the 2–3 last steps would boost the humanists’ analytical capabilities. We explain why the network modeling process is particularly challenging and can lead to distortions of the sources, biases, and traceability problems. We list three main properties that we believe the constructed network should satisfy: alignment with reality/documents (not only with concepts), traceability (from documents to analysis/visualization and back), and simplicity (understandable by most and not more complex than needed). We claim that the model of bipartite dynamic multivariate network with roles allows an effective annotation/encoding of historical sources while satisfying these properties. We provide real-world examples of how this model has been used to answer socio-historical questions using visual analytics tools.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We describe the workflow followed by historians when conducting a Historical Social Network Analysis (HSNA) with five steps: textual sources acquisition, digitization, annotation, network creation, and analysis/visualization. While most analysis and visualization tools only support the last step, we argue that addressing the 2–3 last steps would boost the humanists’ analytical capabilities. We explain why the network modeling process is particularly challenging and can lead to distortions of the sources, biases, and traceability problems. We list three main properties that we believe the constructed network should satisfy: alignment with reality/documents (not only with concepts), traceability (from documents to analysis/visualization and back), and simplicity (understandable by most and not more complex than needed). We claim that the model of bipartite dynamic multivariate network with roles allows an effective annotation/encoding of historical sources while satisfying these properties. We provide real-world examples of how this model has been used to answer socio-historical questions using visual analytics tools.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We describe the workflow followed by historians when conducting a Historical Social Network Analysis (HSNA) with five steps: textual sources acquisition, digitization, annotation, network creation, and analysis/visualization. While most analysis and visualization tools only support the last step, we argue that addressing the 2–3 last steps would boost the humanists’ analytical capabilities. We explain why the network modeling process is particularly challenging and can lead to distortions of the sources, biases, and traceability problems. We list three main properties that we believe the constructed network should satisfy: alignment with reality/documents (not only with concepts), traceability (from documents to analysis/visualization and back), and simplicity (understandable by most and not more complex than needed). We claim that the model of bipartite dynamic multivariate network with roles allows an effective annotation/encoding of historical sources while satisfying these properties. We provide real-world examples of how this model has been used to answer socio-historical questions using visual analytics tools.",
"fno": "766800a037",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Graph Theory",
"History",
"Social Networking Online",
"Bipartite Dynamic Multivariate Network",
"Constructed Network",
"Historical Documents",
"Historical Social Network Analysis",
"Historical Sources",
"Humanists",
"Network Creation",
"Network Modeling Process",
"Social Network Visualization",
"Socio Historical Questions",
"Textual Sources Acquisition",
"Traceability Problems",
"Visual Analytics Tools",
"Visualization Tools",
"Analytical Models",
"Humanities",
"Text Analysis",
"Social Networking Online",
"Annotations",
"Visual Analytics",
"Computational Modeling",
"Applied Computing",
"Arts And Humanities Human Centered Computing",
"Visualization",
"Visualization Application Domains",
"Visual Analytics"
],
"authors": [
{
"affiliation": "Université Paris-Saclay, CNRS, Inria",
"fullName": "Alexis Pister",
"givenName": "Alexis",
"surname": "Pister",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Université Gustave Eiffel",
"fullName": "Nicole Dufournaud",
"givenName": "Nicole",
"surname": "Dufournaud",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "EHESS",
"fullName": "Pascal Cristofoli",
"givenName": "Pascal",
"surname": "Cristofoli",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Institut Polytechnique de Paris",
"fullName": "Christophe Prieur",
"givenName": "Christophe",
"surname": "Prieur",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Université Paris-Saclay, CNRS, Inria",
"fullName": "Jean-Daniel Fekete",
"givenName": "Jean-Daniel",
"surname": "Fekete",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vis4dh",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "37-42",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-7668-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "766800a025",
"articleId": "1J2XI1dX2Q8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "766800a043",
"articleId": "1J2XH4Bdug0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2007/2822/1/28220138",
"title": "Text Line Segmentation of Historical Arabic Documents",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2007/28220138/12OmNAYGlok",
"parentPublication": {
"id": "proceedings/icdar/2007/2822/1",
"title": "Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2015/1805/0/07333935",
"title": "Binarization-free OCR for historical documents using LSTM networks",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2015/07333935/12OmNwl8GFn",
"parentPublication": {
"id": "proceedings/icdar/2015/1805/0",
"title": "2015 13th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2012/4752/0/06400484",
"title": "Relative N-gram signatures: Document visualization at the level of character N-grams",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2012/06400484/12OmNy5hRkw",
"parentPublication": {
"id": "proceedings/vast/2012/4752/0",
"title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2012/4771/0/4771a540",
"title": "Cultural Heritage Cube. A Conceptual Framework for Visual Exhibition Exploration",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2012/4771a540/12OmNzgeLJb",
"parentPublication": {
"id": "proceedings/iv/2012/4771/0",
"title": "2012 16th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2010/06/ttg2010061441",
"title": "Interactive Visualization of Hyperspectral Images of Historical Documents",
"doi": null,
"abstractUrl": "/journal/tg/2010/06/ttg2010061441/13rRUygT7mR",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2022/9062/0/09956471",
"title": "Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2022/09956471/1IHoVchVX0c",
"parentPublication": {
"id": "proceedings/icpr/2022/9062/0",
"title": "2022 26th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2022/7668/0/766800a025",
"title": "Characterizing Uncertainty in the Visual Text Analysis Pipeline",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2022/766800a025/1J2XI1dX2Q8",
"parentPublication": {
"id": "proceedings/vis4dh/2022/7668/0",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2022/7668/0/766800a019",
"title": "Labeling of Cultural Heritage Collections on the Intersection of Visual Analytics and Digital Humanities",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2022/766800a019/1J2XI8P9aLe",
"parentPublication": {
"id": "proceedings/vis4dh/2022/7668/0",
"title": "2022 IEEE 7th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icfhr/2020/9966/0/996600a031",
"title": "Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization",
"doi": null,
"abstractUrl": "/proceedings-article/icfhr/2020/996600a031/1p2VuMaLbnq",
"parentPublication": {
"id": "proceedings/icfhr/2020/9966/0",
"title": "2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis4dh/2020/9153/0/915300a036",
"title": "Externalizing Transformations of Historical Documents: Opportunities for Provenance-Driven Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/vis4dh/2020/915300a036/1pZ0XRm40vu",
"parentPublication": {
"id": "proceedings/vis4dh/2020/9153/0",
"title": "2020 IEEE 5th Workshop on Visualization for the Digital Humanities (VIS4DH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBscCYp",
"title": "2015 IEEE International Conference on Data Mining Workshop (ICDMW)",
"acronym": "icdmw",
"groupId": "1001620",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqJq4nZ",
"doi": "10.1109/ICDMW.2015.56",
"title": "Why do Retailers End Price Promotions: A Study on Duration and Profit Effects of Promotion",
"normalizedTitle": "Why do Retailers End Price Promotions: A Study on Duration and Profit Effects of Promotion",
"abstract": "Evidence shows that price promotion can help small and medium-sized retailers to increase their sales and profits. However, retailers usually stop the promotion after a certain duration. This study tries to explain why retailers discontinue a price promotion. Our approach assumes that overall contributions of price promotion to retailers' profits decrease progressively with time after the promotion begins. We propose simple econometric models to investigate the relationship between promotion duration and the overall effects of price discount on retailers' profits, by using point-of-sale data from Japan's supermarkets. The finding suggests that overall effects of price promotion on retailers' profits have a downward process with the elapsed time. We hope our paper could be helpful for marketers to understand the dynamic profits effects of price promotion, and to set optimal duration of promotions. The paper also discusses management implications and future research directions at the end.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Evidence shows that price promotion can help small and medium-sized retailers to increase their sales and profits. However, retailers usually stop the promotion after a certain duration. This study tries to explain why retailers discontinue a price promotion. Our approach assumes that overall contributions of price promotion to retailers' profits decrease progressively with time after the promotion begins. We propose simple econometric models to investigate the relationship between promotion duration and the overall effects of price discount on retailers' profits, by using point-of-sale data from Japan's supermarkets. The finding suggests that overall effects of price promotion on retailers' profits have a downward process with the elapsed time. We hope our paper could be helpful for marketers to understand the dynamic profits effects of price promotion, and to set optimal duration of promotions. The paper also discusses management implications and future research directions at the end.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Evidence shows that price promotion can help small and medium-sized retailers to increase their sales and profits. However, retailers usually stop the promotion after a certain duration. This study tries to explain why retailers discontinue a price promotion. Our approach assumes that overall contributions of price promotion to retailers' profits decrease progressively with time after the promotion begins. We propose simple econometric models to investigate the relationship between promotion duration and the overall effects of price discount on retailers' profits, by using point-of-sale data from Japan's supermarkets. The finding suggests that overall effects of price promotion on retailers' profits have a downward process with the elapsed time. We hope our paper could be helpful for marketers to understand the dynamic profits effects of price promotion, and to set optimal duration of promotions. The paper also discusses management implications and future research directions at the end.",
"fno": "8493a328",
"keywords": [
"Biological System Modeling",
"Conferences",
"Electronic Mail",
"Data Models",
"Economics",
"Business",
"Data Analysis",
"Point Of Sale Data",
"Promotion Effects",
"Profits",
"Customer Loyalty",
"Number Of Customers",
"Promotion Duration",
"Elapsed Time"
],
"authors": [
{
"affiliation": null,
"fullName": "Zhen Li",
"givenName": "Zhen",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Katsutoshi Yada",
"givenName": "Katsutoshi",
"surname": "Yada",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdmw",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-11-01T00:00:00",
"pubType": "proceedings",
"pages": "328-335",
"year": "2015",
"issn": "2375-9259",
"isbn": "978-1-4673-8493-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "8493a319",
"articleId": "12OmNzl3WOl",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "8493a336",
"articleId": "12OmNxecRWH",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wccct/2014/2877/0/2877a208",
"title": "Improving the Retailers Profit for CRM Using Data Mining Techniques",
"doi": null,
"abstractUrl": "/proceedings-article/wccct/2014/2877a208/12OmNAJDBvt",
"parentPublication": {
"id": "proceedings/wccct/2014/2877/0",
"title": "2014 World Congress on Computing and Communication Technologies (WCCCT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciii/2008/3435/3/3435c252",
"title": "Price Competition between Mobile Commerce Retailers and Traditional Off-Line Retailers when m-Consumers are Loss Averse",
"doi": null,
"abstractUrl": "/proceedings-article/iciii/2008/3435c252/12OmNvvLi56",
"parentPublication": {
"id": "proceedings/iciii/2008/3435/3",
"title": "International Conference on Information Management, Innovation Management and Industrial Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cso/2014/5372/0/5372a621",
"title": "Dynamic Pricing of Duopoly through Pricing Game Based on Price Discrimination",
"doi": null,
"abstractUrl": "/proceedings-article/cso/2014/5372a621/12OmNxXCGIr",
"parentPublication": {
"id": "proceedings/cso/2014/5372/0",
"title": "2014 Seventh International Joint Conference on Computational Sciences and Optimization (CSO)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/1995/6945/0/69450933",
"title": "Modeling an organizational decision support system to improve retailers' decisions",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/1995/69450933/12OmNyz5JS1",
"parentPublication": {
"id": "proceedings/hicss/1995/6945/0",
"title": "28th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmecg/2010/8507/0/05628652",
"title": "The Game Research between a Direct Internet Marketer and N Retailers in Hybrid Marketing",
"doi": null,
"abstractUrl": "/proceedings-article/icmecg/2010/05628652/12OmNzn38RA",
"parentPublication": {
"id": "proceedings/icmecg/2010/8507/0",
"title": "2010 Fourth International Conference on Management of E-Commerce and E-Government (ICMeCG 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2004/2056/8/205680213b",
"title": "Online Price Competition within and between Heterogeneous Retailer Groups",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2004/205680213b/12OmNzvQI7Z",
"parentPublication": {
"id": "proceedings/hicss/2004/2056/8",
"title": "37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2019/01/08332494",
"title": "Finding Optimal Skyline Product Combinations under Price Promotion",
"doi": null,
"abstractUrl": "/journal/tk/2019/01/08332494/17D45XH89p5",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icekim/2022/1666/0/166600a676",
"title": "Research on replenishment model of retailers in community considering replenishment cost rate and service level",
"doi": null,
"abstractUrl": "/proceedings-article/icekim/2022/166600a676/1KpBuW3huO4",
"parentPublication": {
"id": "proceedings/icekim/2022/1666/0",
"title": "2022 3rd International Conference on Education, Knowledge and Information Management (ICEKIM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icuems/2020/8832/0/09151759",
"title": "Research on pricing strategy of omni-channel supply chain led by retailers",
"doi": null,
"abstractUrl": "/proceedings-article/icuems/2020/09151759/1lRlOZkKdna",
"parentPublication": {
"id": "proceedings/icuems/2020/8832/0",
"title": "2020 International Conference on Urban Engineering and Management Science (ICUEMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/msieid/2020/1541/0/154100a187",
"title": "Tests of CBOE Options Market Efficiency and Arbitrage Opportunities Based on Options Pricing Mathematical Models",
"doi": null,
"abstractUrl": "/proceedings-article/msieid/2020/154100a187/1scHJJGcmdy",
"parentPublication": {
"id": "proceedings/msieid/2020/1541/0",
"title": "2020 Management Science Informatization and Economic Innovation Development Conference (MSIEID)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyPQ4uT",
"title": "2009 International Asia Symposium on Intelligent Interaction and Affective Computing",
"acronym": "asia",
"groupId": "1003067",
"volume": "0",
"displayVolume": "0",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyoiZbb",
"doi": "10.1109/ASIA.2009.28",
"title": "An Empirical Study of E-commerce Trust Promotion Strategies Efficiency Based on Chinese Samples",
"normalizedTitle": "An Empirical Study of E-commerce Trust Promotion Strategies Efficiency Based on Chinese Samples",
"abstract": "The insufficiency of consumer’s trust is one of bottlenecks to China online shopping, and now most websites resort to the renowned third party or trust displaying mechanism to promoting consumer’s trust. However, whether the two kinds of trust promotion strategies above have the same effect? And whether their own attributes and assurance contents have the significant influence on consumer’s trust? There are no answers to those questions in domestic research. This article took the third party guarantee and trust displaying strategy as the objects, and collected data of 225 university students through online simulation shopping. Regression analysis was applied to the data and finally got some useful conclusions. The third party guarantee strategy has higher efficiency in promoting consumer’s trust than trust displaying strategy. The provider attributes and assurance contents of the two strategies have positive significant effect on consumer’s trust. Moreover, the attributes of strategies have bigger effect than assurance contents comparatively.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The insufficiency of consumer’s trust is one of bottlenecks to China online shopping, and now most websites resort to the renowned third party or trust displaying mechanism to promoting consumer’s trust. However, whether the two kinds of trust promotion strategies above have the same effect? And whether their own attributes and assurance contents have the significant influence on consumer’s trust? There are no answers to those questions in domestic research. This article took the third party guarantee and trust displaying strategy as the objects, and collected data of 225 university students through online simulation shopping. Regression analysis was applied to the data and finally got some useful conclusions. The third party guarantee strategy has higher efficiency in promoting consumer’s trust than trust displaying strategy. The provider attributes and assurance contents of the two strategies have positive significant effect on consumer’s trust. Moreover, the attributes of strategies have bigger effect than assurance contents comparatively.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The insufficiency of consumer’s trust is one of bottlenecks to China online shopping, and now most websites resort to the renowned third party or trust displaying mechanism to promoting consumer’s trust. However, whether the two kinds of trust promotion strategies above have the same effect? And whether their own attributes and assurance contents have the significant influence on consumer’s trust? There are no answers to those questions in domestic research. This article took the third party guarantee and trust displaying strategy as the objects, and collected data of 225 university students through online simulation shopping. Regression analysis was applied to the data and finally got some useful conclusions. The third party guarantee strategy has higher efficiency in promoting consumer’s trust than trust displaying strategy. The provider attributes and assurance contents of the two strategies have positive significant effect on consumer’s trust. Moreover, the attributes of strategies have bigger effect than assurance contents comparatively.",
"fno": "3910a124",
"keywords": [
"Electronic Commerce",
"Consumers Trust",
"Efficiency",
"Trust Displaying Strategy",
"Third Party Guarantee Strategy"
],
"authors": [
{
"affiliation": null,
"fullName": "Xiao Kaihong",
"givenName": "Xiao",
"surname": "Kaihong",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "asia",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-12-01T00:00:00",
"pubType": "proceedings",
"pages": "124-127",
"year": "2009",
"issn": null,
"isbn": "978-0-7695-3910-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3910a120",
"articleId": "12OmNylbozy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3910a128",
"articleId": "12OmNAkniVL",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wowmom/2011/0352/0/05986201",
"title": "A trust management model for Body Sensor Networks",
"doi": null,
"abstractUrl": "/proceedings-article/wowmom/2011/05986201/12OmNAKcNNU",
"parentPublication": {
"id": "proceedings/wowmom/2011/0352/0",
"title": "2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom/2012/4745/0/4745b423",
"title": "Research on Trust Issue of Current Chinese C2C E-commerce: Problems and Solutions",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom/2012/4745b423/12OmNAle6Gz",
"parentPublication": {
"id": "proceedings/trustcom/2012/4745/0",
"title": "2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdcs/1997/7813/0/78130322",
"title": "Building Trust for Distributed Commerce Transactions",
"doi": null,
"abstractUrl": "/proceedings-article/icdcs/1997/78130322/12OmNBOllrn",
"parentPublication": {
"id": "proceedings/icdcs/1997/7813/0",
"title": "Proceedings of 17th International Conference on Distributed Computing Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iptc/2010/4196/0/4196a101",
"title": "A User-Centric Trust and Reputation Method for Service Selection",
"doi": null,
"abstractUrl": "/proceedings-article/iptc/2010/4196a101/12OmNqH9hna",
"parentPublication": {
"id": "proceedings/iptc/2010/4196/0",
"title": "Intelligence Information Processing and Trusted Computing, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bcgin/2012/4854/0/4854a361",
"title": "Evolution of Transaction Mechanism and Risks Control: Comparision between International E-commerce and Traditional International Trade",
"doi": null,
"abstractUrl": "/proceedings-article/bcgin/2012/4854a361/12OmNqyUUth",
"parentPublication": {
"id": "proceedings/bcgin/2012/4854/0",
"title": "2012 Second International Conference on Business Computing and Global Informatization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2008/3381/0/3381a165",
"title": "Dominant Factors for Online Trust",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2008/3381a165/12OmNwpXRXY",
"parentPublication": {
"id": "proceedings/cw/2008/3381/0",
"title": "2008 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dasc/2011/4612/0/4612a674",
"title": "A Group-Choose Model for Partner Selection in Virtual Organization",
"doi": null,
"abstractUrl": "/proceedings-article/dasc/2011/4612a674/12OmNz5s0Sb",
"parentPublication": {
"id": "proceedings/dasc/2011/4612/0",
"title": "Dependable, Autonomic and Secure Computing, IEEE International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isecs/2009/3643/1/3643a379",
"title": "Intermediating Effect of Knowledge Sharing between Virtual Community System Design and E-commerce Trust: An Empirical Study from China",
"doi": null,
"abstractUrl": "/proceedings-article/isecs/2009/3643a379/12OmNzCWG1G",
"parentPublication": {
"id": "proceedings/isecs/2009/3643/2",
"title": "Electronic Commerce and Security, International Symposium",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icie/2009/3679/1/3679a061",
"title": "How to Cope with Fraud of Trusted Third Party in E-commerce: An Analysis Based on Evolutionary Game Theory",
"doi": null,
"abstractUrl": "/proceedings-article/icie/2009/3679a061/12OmNzYNNds",
"parentPublication": {
"id": "proceedings/icie/2009/3679/1",
"title": "2009 WASE International Conference on Information Engineering (ICIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isme/2010/4132/2/4132b109",
"title": "An Empirical Study of Online Third Party Guarantee Service Effect",
"doi": null,
"abstractUrl": "/proceedings-article/isme/2010/4132b109/12OmNzvQHRm",
"parentPublication": {
"id": "proceedings/isme/2010/4132/2",
"title": "Information Science and Management Engineering, International Conference of",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNwvVrMU",
"title": "2013 Fifth International Conference on Service Science and Innovation (ICSSI)",
"acronym": "icssi",
"groupId": "1802839",
"volume": "0",
"displayVolume": "0",
"year": "2013",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzmLxGR",
"doi": "10.1109/ICSSI.2013.27",
"title": "The Effect of Online Sales Promotion Strategies on Consumers' Perceived Quality and Purchase Intention: A Moderating Effect of Brand Awareness",
"normalizedTitle": "The Effect of Online Sales Promotion Strategies on Consumers' Perceived Quality and Purchase Intention: A Moderating Effect of Brand Awareness",
"abstract": "Along with the explosion of Internet user, Internet has been considered as the new channel for companies implementing their sales promotion activities. Consequently, this study seeks to offer insight into how popular online promotions (price-discount, coupon and free shipping) influence consumer's quality perception and purchase intentions. Moreover, brand awareness was expected to moderate the relationship between promotion and consumer responses. To achieve this objective, a 3 (promotion: price-discount / coupon / free shipping) x 2 (brand: well-known / fictitious brand) between-subjects factorial design experiment was conducted. The participants were 210 college students. The results revealed significant main effects for promotion and brand awareness on consumers' perceived quality. Specifically, in contrast with coupon promotion, price-discount revealed greater impact on consumer's perceived quality. In addition, well-known brand has successfully played a moderating role in the relationship between promotions and consumer responses. The research finding suggested that promotional strategies used by well-known brand are more possible to result in more favorable responses. Findings from this study will be able to provide useful knowledge for online sellers to choose appropriate sales promotion tools to successfully induce consumer's purchase intentions.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Along with the explosion of Internet user, Internet has been considered as the new channel for companies implementing their sales promotion activities. Consequently, this study seeks to offer insight into how popular online promotions (price-discount, coupon and free shipping) influence consumer's quality perception and purchase intentions. Moreover, brand awareness was expected to moderate the relationship between promotion and consumer responses. To achieve this objective, a 3 (promotion: price-discount / coupon / free shipping) x 2 (brand: well-known / fictitious brand) between-subjects factorial design experiment was conducted. The participants were 210 college students. The results revealed significant main effects for promotion and brand awareness on consumers' perceived quality. Specifically, in contrast with coupon promotion, price-discount revealed greater impact on consumer's perceived quality. In addition, well-known brand has successfully played a moderating role in the relationship between promotions and consumer responses. The research finding suggested that promotional strategies used by well-known brand are more possible to result in more favorable responses. Findings from this study will be able to provide useful knowledge for online sellers to choose appropriate sales promotion tools to successfully induce consumer's purchase intentions.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Along with the explosion of Internet user, Internet has been considered as the new channel for companies implementing their sales promotion activities. Consequently, this study seeks to offer insight into how popular online promotions (price-discount, coupon and free shipping) influence consumer's quality perception and purchase intentions. Moreover, brand awareness was expected to moderate the relationship between promotion and consumer responses. To achieve this objective, a 3 (promotion: price-discount / coupon / free shipping) x 2 (brand: well-known / fictitious brand) between-subjects factorial design experiment was conducted. The participants were 210 college students. The results revealed significant main effects for promotion and brand awareness on consumers' perceived quality. Specifically, in contrast with coupon promotion, price-discount revealed greater impact on consumer's perceived quality. In addition, well-known brand has successfully played a moderating role in the relationship between promotions and consumer responses. The research finding suggested that promotional strategies used by well-known brand are more possible to result in more favorable responses. Findings from this study will be able to provide useful knowledge for online sellers to choose appropriate sales promotion tools to successfully induce consumer's purchase intentions.",
"fno": "4985a091",
"keywords": [
"Promotion Marketing",
"Internet",
"Quality Assessment",
"Product Design",
"Educational Institutions",
"Context",
"Companies",
"Brand Awareness",
"Online Sales Promotion",
"Perception Of Quality",
"Purchase Intention"
],
"authors": [
{
"affiliation": null,
"fullName": "Yi-Ting Huang",
"givenName": "Yi-Ting",
"surname": "Huang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Fei-Fei Cheng",
"givenName": "Fei-Fei",
"surname": "Cheng",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icssi",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2013-05-01T00:00:00",
"pubType": "proceedings",
"pages": "91-95",
"year": "2013",
"issn": null,
"isbn": "978-0-7695-4985-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4985a086",
"articleId": "12OmNwJybQ2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4985a096",
"articleId": "12OmNqH9hea",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iiai-aai/2016/8985/0/8985a468",
"title": "Development of Recommendation Engines for Enhancing Sales of DIY (Do It Yourself) Stores",
"doi": null,
"abstractUrl": "/proceedings-article/iiai-aai/2016/8985a468/12OmNCbCrWi",
"parentPublication": {
"id": "proceedings/iiai-aai/2016/8985/0",
"title": "2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icic/2011/688/0/05954605",
"title": "Some Application of Markov Chain to Market Occupation Rate and Promotion Strategy",
"doi": null,
"abstractUrl": "/proceedings-article/icic/2011/05954605/12OmNs59JFI",
"parentPublication": {
"id": "proceedings/icic/2011/688/0",
"title": "2011 Fourth International Conference on Information and Computing (ICIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/waina/2013/4952/0/4952b129",
"title": "A Business Model for Personalized Promotion Systems on Using WLAN Localization and NFC Techniques",
"doi": null,
"abstractUrl": "/proceedings-article/waina/2013/4952b129/12OmNvlg8fB",
"parentPublication": {
"id": "proceedings/waina/2013/4952/0",
"title": "2013 27th International Conference on Advanced Information Networking and Applications Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2016/5670/0/5670d546",
"title": "Do Facebook Likes Lead to Shares or Sales? Exploring the Empirical Links between Social Media Content, Brand Equity, Purchase Intention, and Engagement",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2016/5670d546/12OmNxbW4Pu",
"parentPublication": {
"id": "proceedings/hicss/2016/5670/0",
"title": "2016 49th Hawaii International Conference on System Sciences (HICSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wnis/2009/3901/0/3901a354",
"title": "Study on the Brand Value Promotion of Hotel Service Industry",
"doi": null,
"abstractUrl": "/proceedings-article/wnis/2009/3901a354/12OmNxxvAHa",
"parentPublication": {
"id": "proceedings/wnis/2009/3901/0",
"title": "Wireless Networks and Information Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bcgin/2011/4464/0/4464a200",
"title": "The Core Changes of Promotion Mode in the Era of Knowledge Economy",
"doi": null,
"abstractUrl": "/proceedings-article/bcgin/2011/4464a200/12OmNyuya8i",
"parentPublication": {
"id": "proceedings/bcgin/2011/4464/0",
"title": "2011 International Conference on Business Computing and Global Informatization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fones-aiot/2021/1091/0/109100a120",
"title": "Application Analysis of Artificial Intelligence Technology in Brand Marketing Strategy",
"doi": null,
"abstractUrl": "/proceedings-article/fones-aiot/2021/109100a120/1CKQWvawZEs",
"parentPublication": {
"id": "proceedings/fones-aiot/2021/1091/0",
"title": "2021 International Conference on Forthcoming Networks and Sustainability in AIoT Era (FoNeS-AIoT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aie/2022/7400/0/740000a419",
"title": "Intelligent international marketing system and marketing method based on big data",
"doi": null,
"abstractUrl": "/proceedings-article/aie/2022/740000a419/1GZjawLKbm0",
"parentPublication": {
"id": "proceedings/aie/2022/7400/0",
"title": "2022 International Conference on Artificial Intelligence in Everything (AIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecit/2021/3873/0/387300a404",
"title": "Research on Customer Satisfaction under Two Restrictive Discount Promotion Strategies Based on SPSS analysis software",
"doi": null,
"abstractUrl": "/proceedings-article/ecit/2021/387300a404/1sZ3j9IPKgw",
"parentPublication": {
"id": "proceedings/ecit/2021/3873/0",
"title": "2021 2nd International Conference on E-Commerce and Internet Technology (ECIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icris/2020/1969/0/196900a378",
"title": "A Novel Nongfu Spring's Best Selling Strategy Based on Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/icris/2020/196900a378/1wG5X1hEsUg",
"parentPublication": {
"id": "proceedings/icris/2020/1969/0",
"title": "2020 International Conference on Robots & Intelligent System (ICRIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKisl",
"title": "2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)",
"acronym": "wi",
"groupId": "1001411",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45XoXP6j",
"doi": "10.1109/WI.2018.00-82",
"title": "Pricing Strategies with Promotion Time Limitation in Online Social Networks",
"normalizedTitle": "Pricing Strategies with Promotion Time Limitation in Online Social Networks",
"abstract": "Online social networks provide a platform for customers to share their experience and make viral marketing possible. Through online social networks, sellers can apply marketing strategies to reach more potential buyers and thus gain more revenue. Previous studies on social network marketing based on the influence maximization problem focus on how to propagate information widely and neglect that price is a key factor that influences information diffusion. In this paper, we study the problem of how to design pricing strategies in order to maximize the revenue when the product usage or promotion time is limited. Different from the existing study of optimal pricing scheme over online social networks, we consider how the price may influence the diffusion. In addition, with limited promotion time, the prices assigned in the different promotion stages of the pricing sequence can be increasing. To better understand the problem, we propose a framework which incorporates the influence maximization problem and a multi-state diffusion model. In the diffusion model, users are divided into different groups by their purchasing behavior and have different influence power, which informs how pricing strategies can influence the potential buyers. We design several pricing strategies under our framework with different pricing sequence order and different promotion time. Simulations are performed to illustrate the concepts in our framework and compare different pricing strategies. With our framework, we can provide some guidelines for the seller when designing the pricing strategy.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Online social networks provide a platform for customers to share their experience and make viral marketing possible. Through online social networks, sellers can apply marketing strategies to reach more potential buyers and thus gain more revenue. Previous studies on social network marketing based on the influence maximization problem focus on how to propagate information widely and neglect that price is a key factor that influences information diffusion. In this paper, we study the problem of how to design pricing strategies in order to maximize the revenue when the product usage or promotion time is limited. Different from the existing study of optimal pricing scheme over online social networks, we consider how the price may influence the diffusion. In addition, with limited promotion time, the prices assigned in the different promotion stages of the pricing sequence can be increasing. To better understand the problem, we propose a framework which incorporates the influence maximization problem and a multi-state diffusion model. In the diffusion model, users are divided into different groups by their purchasing behavior and have different influence power, which informs how pricing strategies can influence the potential buyers. We design several pricing strategies under our framework with different pricing sequence order and different promotion time. Simulations are performed to illustrate the concepts in our framework and compare different pricing strategies. With our framework, we can provide some guidelines for the seller when designing the pricing strategy.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Online social networks provide a platform for customers to share their experience and make viral marketing possible. Through online social networks, sellers can apply marketing strategies to reach more potential buyers and thus gain more revenue. Previous studies on social network marketing based on the influence maximization problem focus on how to propagate information widely and neglect that price is a key factor that influences information diffusion. In this paper, we study the problem of how to design pricing strategies in order to maximize the revenue when the product usage or promotion time is limited. Different from the existing study of optimal pricing scheme over online social networks, we consider how the price may influence the diffusion. In addition, with limited promotion time, the prices assigned in the different promotion stages of the pricing sequence can be increasing. To better understand the problem, we propose a framework which incorporates the influence maximization problem and a multi-state diffusion model. In the diffusion model, users are divided into different groups by their purchasing behavior and have different influence power, which informs how pricing strategies can influence the potential buyers. We design several pricing strategies under our framework with different pricing sequence order and different promotion time. Simulations are performed to illustrate the concepts in our framework and compare different pricing strategies. With our framework, we can provide some guidelines for the seller when designing the pricing strategy.",
"fno": "732500a254",
"keywords": [
"Consumer Behaviour",
"Internet",
"Marketing Data Processing",
"Optimisation",
"Pricing",
"Promotion Marketing",
"Purchasing",
"Social Networking Online",
"Promotion Time Limitation",
"Online Social Networks",
"Marketing Strategies",
"Social Network Marketing",
"Optimal Pricing Scheme",
"Pricing Strategies",
"Influence Maximization Problem",
"Promotion Stages",
"Pricing Sequence Order",
"Purchasing Behavior",
"Pricing",
"Social Network Services",
"Integrated Circuit Modeling",
"Guidelines",
"Cost Accounting",
"Consumer Electronics",
"Pricing",
"Revenue Maximization",
"Online Social Network",
"Limited Promotion Time"
],
"authors": [
{
"affiliation": null,
"fullName": "Yan Li",
"givenName": "Yan",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Victor O.K. Li",
"givenName": "Victor O.K.",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wi",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-12-01T00:00:00",
"pubType": "proceedings",
"pages": "254-261",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-7325-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "732500a246",
"articleId": "17D45WaTkjr",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "732500a262",
"articleId": "17D45XuDNG3",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/focs/2009/5116/0/05438605",
"title": "Dynamic and Non-uniform Pricing Strategies for Revenue Maximization",
"doi": null,
"abstractUrl": "/proceedings-article/focs/2009/05438605/12OmNB7tUsk",
"parentPublication": {
"id": "proceedings/focs/2009/5116/0",
"title": "2009 50th Annual IEEE Symposium on Foundations of Computer Science",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bife/2012/4750/0/4750a073",
"title": "Competitive Pricing Strategy Based on Consumer Stockpiling and Consumption Acceleration Behaviors",
"doi": null,
"abstractUrl": "/proceedings-article/bife/2012/4750a073/12OmNwDACte",
"parentPublication": {
"id": "proceedings/bife/2012/4750/0",
"title": "2012 Fifth International Conference on Business Intelligence and Financial Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2013/4892/0/4892e136",
"title": "Design of Consumer Review Systems and Product Pricing",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2013/4892e136/12OmNwG90ev",
"parentPublication": {
"id": "proceedings/hicss/2013/4892/0",
"title": "2013 46th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiai-aai/2017/0621/0/0621a041",
"title": "Pricing Strategies and Decisions in a Bertrand Competition with Markov Process",
"doi": null,
"abstractUrl": "/proceedings-article/iiai-aai/2017/0621a041/12OmNwO5LUk",
"parentPublication": {
"id": "proceedings/iiai-aai/2017/0621/0",
"title": "2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi-iat/2011/4513/2/4513b323",
"title": "Adaptive Strategies for Dynamic Pricing Agents",
"doi": null,
"abstractUrl": "/proceedings-article/wi-iat/2011/4513b323/12OmNwdbV23",
"parentPublication": {
"id": "proceedings/wi-iat/2011/4513/2",
"title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccms/2010/5642/2/05421144",
"title": "A Dynamic Pricing Algorithm by Bayesian Q-learning",
"doi": null,
"abstractUrl": "/proceedings-article/iccms/2010/05421144/12OmNxdVgHU",
"parentPublication": {
"id": "proceedings/iccms/2010/5642/2",
"title": "2010 Second International Conference on Computer Modeling and Simulation (ICCMS 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/edoc/2017/3045/0/3045a061",
"title": "An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces",
"doi": null,
"abstractUrl": "/proceedings-article/edoc/2017/3045a061/12OmNzYeB4e",
"parentPublication": {
"id": "proceedings/edoc/2017/3045/0",
"title": "2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2007/2755/0/04076803",
"title": "Using Online Competitor's Inventory Information for Pricing",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2007/04076803/17D45Xtvpb3",
"parentPublication": {
"id": "proceedings/hicss/2007/2755/0",
"title": "2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icemme/2019/5588/0/558800a603",
"title": "Research on Two-Stage Pricing Strategy of Fresh Products Based on Consumer Types",
"doi": null,
"abstractUrl": "/proceedings-article/icemme/2019/558800a603/1hrLkBusqIg",
"parentPublication": {
"id": "proceedings/icemme/2019/5588/0",
"title": "2019 International Conference on Economic Management and Model Engineering (ICEMME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icecem/2021/1025/0/102500a201",
"title": "Seller's Pricing Discrimination Strategies under Adoption of Online Big Data Technology",
"doi": null,
"abstractUrl": "/proceedings-article/icecem/2021/102500a201/1zpEOYbkzqo",
"parentPublication": {
"id": "proceedings/icecem/2021/1025/0",
"title": "2021 International Conference on E-Commerce and E-Management (ICECEM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1Lxfm4fufy8",
"title": "2022 2nd International Conference on Computer Graphics, Image and Virtualization (ICCGIV)",
"acronym": "iccgiv",
"groupId": "10062267",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1Lxfou1rKKI",
"doi": "10.1109/ICCGIV57403.2022.00045",
"title": "Sales Forecasting Model of E-commerce Activities Based on Improved Random Forest Algorithm",
"normalizedTitle": "Sales Forecasting Model of E-commerce Activities Based on Improved Random Forest Algorithm",
"abstract": "The accuracy of commodity sales forecast is related to the profits of all stakeholders. But shortages and overstocking are widespread, posing a dilemma for retailers: They need to balance losses from shortages with the cost of safe stocking. This paper mainly studies the data mining algorithm for mobile e-commerce activity sales forecasting model. This paper first introduces the concept of data mining, and improves the random forest algorithm in the data mining algorithm, and puts forward the method of Bayesian optimization combined with time series segmentation to optimize the random forest model, so as to achieve the purpose of improving the prediction effect. Based on the improved random forest algorithm, this paper established the sales prediction model of mobile e-commerce. Through the analysis of the results of the prediction model, it can be seen that the prediction error of the prediction model is larger for food and clothing whose sales are greatly affected by activities, and smaller for tools whose sales are less affected by activities.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The accuracy of commodity sales forecast is related to the profits of all stakeholders. But shortages and overstocking are widespread, posing a dilemma for retailers: They need to balance losses from shortages with the cost of safe stocking. This paper mainly studies the data mining algorithm for mobile e-commerce activity sales forecasting model. This paper first introduces the concept of data mining, and improves the random forest algorithm in the data mining algorithm, and puts forward the method of Bayesian optimization combined with time series segmentation to optimize the random forest model, so as to achieve the purpose of improving the prediction effect. Based on the improved random forest algorithm, this paper established the sales prediction model of mobile e-commerce. Through the analysis of the results of the prediction model, it can be seen that the prediction error of the prediction model is larger for food and clothing whose sales are greatly affected by activities, and smaller for tools whose sales are less affected by activities.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The accuracy of commodity sales forecast is related to the profits of all stakeholders. But shortages and overstocking are widespread, posing a dilemma for retailers: They need to balance losses from shortages with the cost of safe stocking. This paper mainly studies the data mining algorithm for mobile e-commerce activity sales forecasting model. This paper first introduces the concept of data mining, and improves the random forest algorithm in the data mining algorithm, and puts forward the method of Bayesian optimization combined with time series segmentation to optimize the random forest model, so as to achieve the purpose of improving the prediction effect. Based on the improved random forest algorithm, this paper established the sales prediction model of mobile e-commerce. Through the analysis of the results of the prediction model, it can be seen that the prediction error of the prediction model is larger for food and clothing whose sales are greatly affected by activities, and smaller for tools whose sales are less affected by activities.",
"fno": "925000a195",
"keywords": [
"Data Mining",
"Electronic Commerce",
"Forecasting Theory",
"Profitability",
"Random Forests",
"Sales Management",
"Time Series",
"Commodity Sales Forecast",
"Data Mining Algorithm",
"E Commerce Activities",
"Improved Random Forest Algorithm",
"Mobile E Commerce Activity Sales Forecasting Model",
"Random Forest Model",
"Sales Prediction Model",
"Shortages",
"Analytical Models",
"Time Series Analysis",
"Predictive Models",
"Prediction Algorithms",
"Data Models",
"Electronic Commerce",
"Data Mining",
"Mobile E Commerce",
"Sales Forecasting",
"Random Forest Algorithm"
],
"authors": [
{
"affiliation": "Lyceum of the Philippines University,Manila,Philippines",
"fullName": "Shuang Li",
"givenName": "Shuang",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccgiv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-09-01T00:00:00",
"pubType": "proceedings",
"pages": "195-198",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-9250-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "925000a191",
"articleId": "1Lxfn0Al4Wc",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "925000a199",
"articleId": "1LxfmPrJ1te",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/soca/2016/4781/0/4781a010",
"title": "A Novel Prediction Model for Sales Forecasting Based on Grey System",
"doi": null,
"abstractUrl": "/proceedings-article/soca/2016/4781a010/12OmNCmpcKi",
"parentPublication": {
"id": "proceedings/soca/2016/4781/0",
"title": "2016 IEEE 9th Conference on Service-Oriented Computing and Applications (SOCA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apwc-on-cse/2017/4530/0/08487259",
"title": "Do Sales Promotions Affect Dynamic Changes in Sales Outcomes: Estimation of Dynamic State of Product Sales",
"doi": null,
"abstractUrl": "/proceedings-article/apwc-on-cse/2017/08487259/17D45WHONkk",
"parentPublication": {
"id": "proceedings/apwc-on-cse/2017/4530/0",
"title": "2017 4th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisce/2018/5500/0/550000a552",
"title": "The Electricity Sales Forecasting Based on Leading Analysis and Factor Compensation",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2018/550000a552/17D45Wuc38c",
"parentPublication": {
"id": "proceedings/icisce/2018/5500/0",
"title": "2018 5th International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdacai/2022/5470/0/547000a261",
"title": "Research on RF-NMF dimension reduction and CS-LSTM optimized by self-attention mechanism based on sales forecast",
"doi": null,
"abstractUrl": "/proceedings-article/icdacai/2022/547000a261/1J7WYoWRXBC",
"parentPublication": {
"id": "proceedings/icdacai/2022/5470/0",
"title": "2022 International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icemme/2019/5588/0/558800a307",
"title": "A Neural Network Model for China B2C E-Commerce Sales Forecast Based on Promotional Factors and Historical Data",
"doi": null,
"abstractUrl": "/proceedings-article/icemme/2019/558800a307/1hrLmLFCaT6",
"parentPublication": {
"id": "proceedings/icemme/2019/5588/0",
"title": "2019 International Conference on Economic Management and Model Engineering (ICEMME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isctt/2020/8575/0/857500a336",
"title": "A forecasting method of pharmaceutical sales based on ARIMA-LSTM model",
"doi": null,
"abstractUrl": "/proceedings-article/isctt/2020/857500a336/1rHeQMsRZgk",
"parentPublication": {
"id": "proceedings/isctt/2020/8575/0",
"title": "2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mlbdbi/2020/9638/0/963800a305",
"title": "Research on Refined Sales Management, Data Analysis and Forecasting under Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/mlbdbi/2020/963800a305/1rxhvlzyUyA",
"parentPublication": {
"id": "proceedings/mlbdbi/2020/9638/0",
"title": "2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbase/2020/9619/0/961900a458",
"title": "Walmart Sales Forecasting using XGBoost algorithm and Feature engineering",
"doi": null,
"abstractUrl": "/proceedings-article/icbase/2020/961900a458/1t2nz8wcGLm",
"parentPublication": {
"id": "proceedings/icbase/2020/9619/0",
"title": "2020 International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itca/2020/0378/0/037800a636",
"title": "Sales Forecasting Based on CatBoost",
"doi": null,
"abstractUrl": "/proceedings-article/itca/2020/037800a636/1tpBbrORe5W",
"parentPublication": {
"id": "proceedings/itca/2020/0378/0",
"title": "2020 2nd International Conference on Information Technology and Computer Application (ITCA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccsmt/2020/8668/0/866800a393",
"title": "Automatic Sales Forecasting System Based On LSTM Network",
"doi": null,
"abstractUrl": "/proceedings-article/iccsmt/2020/866800a393/1u8pyADNk1a",
"parentPublication": {
"id": "proceedings/iccsmt/2020/8668/0",
"title": "2020 International Conference on Computer Science and Management Technology (ICCSMT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1gAwR0WCegU",
"title": "2019 International Conference on Data Mining Workshops (ICDMW)",
"acronym": "icdmw",
"groupId": "1001620",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1gAwUrp5uqQ",
"doi": "10.1109/ICDMW.2019.00158",
"title": "Loyal Consumers or One-Time Deal Hunters: Repeat Buyer Prediction for E-Commerce",
"normalizedTitle": "Loyal Consumers or One-Time Deal Hunters: Repeat Buyer Prediction for E-Commerce",
"abstract": "Merchants sometimes run big promotions (e.g., discounts or cash coupons) on particular dates (e.g., Boxing-day Sales, \"Black Friday\" or \"Double 11 (Nov 11th)\", in order to attract a large number of new buyers. Unfortunately, many of the attracted buyers are one-time deal hunters, and these promotions may have little long lasting impact on sales. To alleviate this problem, it is important for merchants to identify who can be converted into repeated buyers. By targeting on these potential loyal customers, merchants can greatly reduce the promotion cost and enhance the return on investment (ROI). It is well known that in the field of online advertising, customer targeting is extremely challenging, especially for fresh buyers. With the long-term user behavior log accumulated by Tmall.com, we get a set of merchants and their corresponding new buyers acquired during the promotion on the \"Double 11\" day. Our goal is to predict which new buyers for given merchants will become loyal customers in the future. In other words, we need to predict the probability that these new buyers would purchase items from the same merchants again within 6 months. A data set containing around 200k users is given for training, while the other of similar size for testing. We extracted as many features as possible and find the key features to train our models. We proposed merged model of different classification models and merged lightGBM model with different parameter sets. The experimental results show that our merged models can bring about great performance improvements comparing with the original models.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Merchants sometimes run big promotions (e.g., discounts or cash coupons) on particular dates (e.g., Boxing-day Sales, \"Black Friday\" or \"Double 11 (Nov 11th)\", in order to attract a large number of new buyers. Unfortunately, many of the attracted buyers are one-time deal hunters, and these promotions may have little long lasting impact on sales. To alleviate this problem, it is important for merchants to identify who can be converted into repeated buyers. By targeting on these potential loyal customers, merchants can greatly reduce the promotion cost and enhance the return on investment (ROI). It is well known that in the field of online advertising, customer targeting is extremely challenging, especially for fresh buyers. With the long-term user behavior log accumulated by Tmall.com, we get a set of merchants and their corresponding new buyers acquired during the promotion on the \"Double 11\" day. Our goal is to predict which new buyers for given merchants will become loyal customers in the future. In other words, we need to predict the probability that these new buyers would purchase items from the same merchants again within 6 months. A data set containing around 200k users is given for training, while the other of similar size for testing. We extracted as many features as possible and find the key features to train our models. We proposed merged model of different classification models and merged lightGBM model with different parameter sets. The experimental results show that our merged models can bring about great performance improvements comparing with the original models.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Merchants sometimes run big promotions (e.g., discounts or cash coupons) on particular dates (e.g., Boxing-day Sales, \"Black Friday\" or \"Double 11 (Nov 11th)\", in order to attract a large number of new buyers. Unfortunately, many of the attracted buyers are one-time deal hunters, and these promotions may have little long lasting impact on sales. To alleviate this problem, it is important for merchants to identify who can be converted into repeated buyers. By targeting on these potential loyal customers, merchants can greatly reduce the promotion cost and enhance the return on investment (ROI). It is well known that in the field of online advertising, customer targeting is extremely challenging, especially for fresh buyers. With the long-term user behavior log accumulated by Tmall.com, we get a set of merchants and their corresponding new buyers acquired during the promotion on the \"Double 11\" day. Our goal is to predict which new buyers for given merchants will become loyal customers in the future. In other words, we need to predict the probability that these new buyers would purchase items from the same merchants again within 6 months. A data set containing around 200k users is given for training, while the other of similar size for testing. We extracted as many features as possible and find the key features to train our models. We proposed merged model of different classification models and merged lightGBM model with different parameter sets. The experimental results show that our merged models can bring about great performance improvements comparing with the original models.",
"fno": "489600b080",
"keywords": [
"Customer Services",
"Data Analysis",
"Electronic Commerce",
"Feature Extraction",
"Internet",
"Investment",
"Learning Artificial Intelligence",
"Marketing Data Processing",
"Pattern Classification",
"Probability",
"Promotion Marketing",
"Purchasing",
"Retail Data Processing",
"Potential Loyal Customers",
"Fresh Buyers",
"One Time Deal Hunters",
"Repeat Buyer Prediction",
"E Commerce",
"Return On Investment",
"ROI",
"Long Term User Behavior Log",
"Probability Prediction",
"Feature Extraction",
"Classification Models",
"Merged Light GBM Model",
"Parameter Sets",
"Online Advertising",
"Promotion Cost Reduction",
"Time 6 0 Month",
"Feature Extraction",
"Training",
"Task Analysis",
"Testing",
"Advertising",
"Data Mining",
"Investment",
"Repeat Buyer Prediction E Commerce Feature Engineering Consumption Patterns"
],
"authors": [
{
"affiliation": "Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen",
"fullName": "Bo Zhao",
"givenName": "Bo",
"surname": "Zhao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "National Institute of Informatics",
"fullName": "Atsuhiro Takasu",
"givenName": "Atsuhiro",
"surname": "Takasu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen",
"fullName": "Ramin Yahyapour",
"givenName": "Ramin",
"surname": "Yahyapour",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Göttingen",
"fullName": "Xiaoming Fu",
"givenName": "Xiaoming",
"surname": "Fu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdmw",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-11-01T00:00:00",
"pubType": "proceedings",
"pages": "1080-1087",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-4896-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "489600b072",
"articleId": "1gAwTux1APe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "489600b088",
"articleId": "1gAwVAjY1gc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdm/2014/4302/0/4302a120",
"title": "Sparse Real Estate Ranking with Online User Reviews and Offline Moving Behaviors",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2014/4302a120/12OmNzuIjpE",
"parentPublication": {
"id": "proceedings/icdm/2014/4302/0",
"title": "2014 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ispa-iucc/2017/3790/0/379001b047",
"title": "Understanding Users' Coupon Usage Behaviors in E-Commerce Environments",
"doi": null,
"abstractUrl": "/proceedings-article/ispa-iucc/2017/379001b047/17D45XeKgo3",
"parentPublication": {
"id": "proceedings/ispa-iucc/2017/3790/0",
"title": "2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpads/2018/7308/0/08645042",
"title": "A Heuristic Approach for Website Classification with Mixed Feature Extractors",
"doi": null,
"abstractUrl": "/proceedings-article/icpads/2018/08645042/17QjJbuI5Fu",
"parentPublication": {
"id": "proceedings/icpads/2018/7308/0",
"title": "2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313234",
"title": "Chemical-protein Interaction Extraction via ChemicalBERT and Attention Guided Graph Convolutional Networks in Parallel",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313234/1qmg5Enlawg",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552250",
"title": "VideoModerator: A Risk-aware Framework for Multimodal Video Moderation in E-Commerce",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552250/1xic6GuRQ76",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1hrLhlar4xa",
"title": "2019 International Conference on Economic Management and Model Engineering (ICEMME)",
"acronym": "icemme",
"groupId": "1835284",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1hrLmLFCaT6",
"doi": "10.1109/ICEMME49371.2019.00067",
"title": "A Neural Network Model for China B2C E-Commerce Sales Forecast Based on Promotional Factors and Historical Data",
"normalizedTitle": "A Neural Network Model for China B2C E-Commerce Sales Forecast Based on Promotional Factors and Historical Data",
"abstract": "Sales forecast is the basis and premise of supply chain management. It affects enterprise inventory level and supply chain operational efficiency. With the rapid development of online shopping, B2C e-commerce enterprises have an increasingly strong demand for accurate and efficient sales forecasting. Influenced by various promotional activities, B2C e-commerce sales in China are characterized by big fluctuations, fast pace and difficult prediction. The problem of sales forecast considering the influence of promotion is an important problem to be solved. This paper combines the characteristics of B2C e-commerce promotion in China and a quantitative model of the influence of promotion on B2C e-commerce sales is established. Based on promotion factors and historical data, we constructed a BP neural network model for B2C e-commerce sales forecast to solve the problem that e-commerce sales are difficult to predict accurately under promotional activities. Through the verification of Alibaba's actual case, it is concluded that the GA-BP algorithm model has a good adaptability to sales forecasting and it achieved 94 percent accuracy. The B2C e-commerce sales forecast model based on sales promotion and historical data established in this paper has high application value.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Sales forecast is the basis and premise of supply chain management. It affects enterprise inventory level and supply chain operational efficiency. With the rapid development of online shopping, B2C e-commerce enterprises have an increasingly strong demand for accurate and efficient sales forecasting. Influenced by various promotional activities, B2C e-commerce sales in China are characterized by big fluctuations, fast pace and difficult prediction. The problem of sales forecast considering the influence of promotion is an important problem to be solved. This paper combines the characteristics of B2C e-commerce promotion in China and a quantitative model of the influence of promotion on B2C e-commerce sales is established. Based on promotion factors and historical data, we constructed a BP neural network model for B2C e-commerce sales forecast to solve the problem that e-commerce sales are difficult to predict accurately under promotional activities. Through the verification of Alibaba's actual case, it is concluded that the GA-BP algorithm model has a good adaptability to sales forecasting and it achieved 94 percent accuracy. The B2C e-commerce sales forecast model based on sales promotion and historical data established in this paper has high application value.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Sales forecast is the basis and premise of supply chain management. It affects enterprise inventory level and supply chain operational efficiency. With the rapid development of online shopping, B2C e-commerce enterprises have an increasingly strong demand for accurate and efficient sales forecasting. Influenced by various promotional activities, B2C e-commerce sales in China are characterized by big fluctuations, fast pace and difficult prediction. The problem of sales forecast considering the influence of promotion is an important problem to be solved. This paper combines the characteristics of B2C e-commerce promotion in China and a quantitative model of the influence of promotion on B2C e-commerce sales is established. Based on promotion factors and historical data, we constructed a BP neural network model for B2C e-commerce sales forecast to solve the problem that e-commerce sales are difficult to predict accurately under promotional activities. Through the verification of Alibaba's actual case, it is concluded that the GA-BP algorithm model has a good adaptability to sales forecasting and it achieved 94 percent accuracy. The B2C e-commerce sales forecast model based on sales promotion and historical data established in this paper has high application value.",
"fno": "558800a307",
"keywords": [
"Backpropagation",
"Electronic Commerce",
"Genetic Algorithms",
"Internet",
"Neural Nets",
"Promotion Marketing",
"Retail Data Processing",
"Sales Management",
"Supply Chain Management",
"Promotional Factors",
"Historical Data",
"Enterprise Inventory Level",
"Supply Chain Operational Efficiency",
"B 2 C E Commerce Enterprises",
"B 2 C E Commerce Promotion",
"BP Neural Network Model",
"Sales Promotion",
"B 2 C E Commerce Sales Forecast",
"Supply Chain Management",
"Online Shopping",
"China",
"GA BP Algorithm Model",
"Predictive Models",
"Indexes",
"Prediction Algorithms",
"Data Models",
"Forecasting",
"Business",
"Time Series Analysis",
"Neural Network",
"Machine Learning",
"GA BP Algorithm",
"Sales Forecast",
"Promotion Analysis",
"Impact Quantification"
],
"authors": [
{
"affiliation": "Beijing Jiaotong University",
"fullName": "Qianwen Zhuang",
"givenName": "Qianwen",
"surname": "Zhuang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beijing Jiaotong University",
"fullName": "Xiaodong Zhang",
"givenName": "Xiaodong",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Bremen",
"fullName": "Pei Wang",
"givenName": "Pei",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TrendChina Co.",
"fullName": "Bin Deng",
"givenName": "Bin",
"surname": "Deng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TrendChina Co.",
"fullName": "Hua Pan",
"givenName": "Hua",
"surname": "Pan",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icemme",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-12-01T00:00:00",
"pubType": "proceedings",
"pages": "307-312",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-5588-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "558800a302",
"articleId": "1hrLkWfa7kI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "558800a313",
"articleId": "1hrLodftHTq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icicta/2014/6636/0/6636a341",
"title": "Logistic Growth Prediction of B2C E-Commerce Based on Nonlinear Integral",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2014/6636a341/12OmNApLGv5",
"parentPublication": {
"id": "proceedings/icicta/2014/6636/0",
"title": "2014 7th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isee/2002/7214/0/01003235",
"title": "Energy efficiency of b2c e-commerce in Japan",
"doi": null,
"abstractUrl": "/proceedings-article/isee/2002/01003235/12OmNwCsdQo",
"parentPublication": {
"id": "proceedings/isee/2002/7214/0",
"title": "Conference Record 2002 IEEE International Symposium on Electronics and the Environment",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2001/0981/0/00926559",
"title": "Health care B2C electronic commerce: what do patients/consumers want?",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2001/00926559/12OmNwtn3uZ",
"parentPublication": {
"id": "proceedings/hicss/2001/0981/2",
"title": "Proceedings of the 34th Annual Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cso/2014/5372/0/5372a602",
"title": "A Novel Forecasting Method for Large-Scale Sales Prediction Using Extreme Learning Machine",
"doi": null,
"abstractUrl": "/proceedings-article/cso/2014/5372a602/12OmNxFJXON",
"parentPublication": {
"id": "proceedings/cso/2014/5372/0",
"title": "2014 Seventh International Joint Conference on Computational Sciences and Optimization (CSO)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2014/04/mex2014040102",
"title": "A Smart B2C e-Commerce System Based on ACP Approach",
"doi": null,
"abstractUrl": "/magazine/ex/2014/04/mex2014040102/13rRUyY290F",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdsba/2018/8431/0/843100a488",
"title": "Game Analysis on Sales Return Involving B2C E-Commerce Seller, Buyer and Platform",
"doi": null,
"abstractUrl": "/proceedings-article/icdsba/2018/843100a488/17D45VsBU06",
"parentPublication": {
"id": "proceedings/icdsba/2018/8431/0",
"title": "2018 2nd International Conference on Data Science and Business Analytics (ICDSBA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccgiv/2022/9250/0/925000a195",
"title": "Sales Forecasting Model of E-commerce Activities Based on Improved Random Forest Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/iccgiv/2022/925000a195/1Lxfou1rKKI",
"parentPublication": {
"id": "proceedings/iccgiv/2022/9250/0",
"title": "2022 2nd International Conference on Computer Graphics, Image and Virtualization (ICCGIV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecit/2021/3873/0/387300a410",
"title": "Sales Prediction based on Machine Learning",
"doi": null,
"abstractUrl": "/proceedings-article/ecit/2021/387300a410/1sZ3gOHvS4U",
"parentPublication": {
"id": "proceedings/ecit/2021/3873/0",
"title": "2021 2nd International Conference on E-Commerce and Internet Technology (ECIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icemme/2020/9144/0/914400a521",
"title": "Forecast Rossmann Store Sales Base on Xgboost Model",
"doi": null,
"abstractUrl": "/proceedings-article/icemme/2020/914400a521/1tV9fcNmyhW",
"parentPublication": {
"id": "proceedings/icemme/2020/9144/0",
"title": "2020 2nd International Conference on Economic Management and Model Engineering (ICEMME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icitbs/2021/4854/0/485400a462",
"title": "Design and Implementation of B2C Agricultural Products E-commerce Sales Platform Based on MVC Mode",
"doi": null,
"abstractUrl": "/proceedings-article/icitbs/2021/485400a462/1wB6MB926oU",
"parentPublication": {
"id": "proceedings/icitbs/2021/4854/0",
"title": "2021 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1lgPDVHZurm",
"title": "2020 International Conference on E-Commerce and Internet Technology (ECIT)",
"acronym": "ecit",
"groupId": "1837104",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1lgPHzbaKgE",
"doi": "10.1109/ECIT50008.2020.00069",
"title": "WeChat Applet Promotion Strategies of Small Shops",
"normalizedTitle": "WeChat Applet Promotion Strategies of Small Shops",
"abstract": "Since being launched in 2017, the WeChat applet (or WeChat mini-program) has won wide popularity and given rise to a new field of online marketing by dint of its convenient loading functions and support from WeChat's large user base. WeChat applets have greatly facilitated connection between online and offline business, and revolutionary changes to small brick-and-mortar stores in particular. Compared with small and medium-sized stores, small stores know little about promotion on WeChat applets. Case studies on applet promotion of several small stores revealed that traditional website promotion strategies and app promotion strategies are not applicable to WeChat applet promotion. To promote small stores on WeChat applets, multiple promotion strategies including online, offline and free promotion strategies should be combined, and the customers' social network should be taken as the key point of network promotion. This paper makes an in-depth analysis of the promotion strategies of small stores on WeChat applets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Since being launched in 2017, the WeChat applet (or WeChat mini-program) has won wide popularity and given rise to a new field of online marketing by dint of its convenient loading functions and support from WeChat's large user base. WeChat applets have greatly facilitated connection between online and offline business, and revolutionary changes to small brick-and-mortar stores in particular. Compared with small and medium-sized stores, small stores know little about promotion on WeChat applets. Case studies on applet promotion of several small stores revealed that traditional website promotion strategies and app promotion strategies are not applicable to WeChat applet promotion. To promote small stores on WeChat applets, multiple promotion strategies including online, offline and free promotion strategies should be combined, and the customers' social network should be taken as the key point of network promotion. This paper makes an in-depth analysis of the promotion strategies of small stores on WeChat applets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Since being launched in 2017, the WeChat applet (or WeChat mini-program) has won wide popularity and given rise to a new field of online marketing by dint of its convenient loading functions and support from WeChat's large user base. WeChat applets have greatly facilitated connection between online and offline business, and revolutionary changes to small brick-and-mortar stores in particular. Compared with small and medium-sized stores, small stores know little about promotion on WeChat applets. Case studies on applet promotion of several small stores revealed that traditional website promotion strategies and app promotion strategies are not applicable to WeChat applet promotion. To promote small stores on WeChat applets, multiple promotion strategies including online, offline and free promotion strategies should be combined, and the customers' social network should be taken as the key point of network promotion. This paper makes an in-depth analysis of the promotion strategies of small stores on WeChat applets.",
"fno": "590200a273",
"keywords": [
"Advertising Data Processing",
"Social Networking Online",
"Applet Promotion Strategies",
"App Promotion Strategies",
"We Chat Applet Promotion",
"Free Promotion Strategies",
"Website Promotion Strategies",
"Social Networking Online",
"Loading",
"Message Service",
"Internet",
"Electronic Commerce",
"Business",
"We Chat Applet Promotion",
"Network Marketing",
"Mobile E Commerce"
],
"authors": [
{
"affiliation": "ShanDong Polytechnic College",
"fullName": "Peng Li",
"givenName": "Peng",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ecit",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-04-01T00:00:00",
"pubType": "proceedings",
"pages": "273-276",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-5902-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "590200a265",
"articleId": "1lgPJHTdfGM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "590200a277",
"articleId": "1lgPHd4Joha",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icse/2022/9221/0/922100a363",
"title": "Characterizing and Detecting Bugs in WeChat Mini-Programs",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2022/922100a363/1EmrXZVtMoE",
"parentPublication": {
"id": "proceedings/icse/2022/9221/0",
"title": "2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictech/2022/9694/0/969400a503",
"title": "Design and Implementation of Shared Book System Based on Wechat Applet",
"doi": null,
"abstractUrl": "/proceedings-article/ictech/2022/969400a503/1FWmBgVJMo8",
"parentPublication": {
"id": "proceedings/ictech/2022/9694/0",
"title": "2022 11th International Conference of Information and Communication Technology (ICTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnisc/2022/5351/0/535100a748",
"title": "Design and Implementation of Aquarium AI System Based on Raspberry Pie",
"doi": null,
"abstractUrl": "/proceedings-article/icnisc/2022/535100a748/1KYt5trs8gg",
"parentPublication": {
"id": "proceedings/icnisc/2022/5351/0",
"title": "2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiam/2022/6399/0/639900a108",
"title": "Design and Implementation of Lab Reservation System Based on Applet",
"doi": null,
"abstractUrl": "/proceedings-article/aiam/2022/639900a108/1LRlKc1ECNW",
"parentPublication": {
"id": "proceedings/aiam/2022/6399/0",
"title": "2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2020/9234/0/923400a191",
"title": "Fusing Multi-Features for Rumor tweets detection in Wechat",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2020/923400a191/1uGXVtMO3yE",
"parentPublication": {
"id": "proceedings/icdh/2020/9234/0",
"title": "2020 8th International Conference on Digital Home (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsgea/2021/3263/0/326300a481",
"title": "Design and Implementation of the Questionnaire WeChat Applet for the Climate Index of SMEs",
"doi": null,
"abstractUrl": "/proceedings-article/icsgea/2021/326300a481/1vb9onfihrO",
"parentPublication": {
"id": "proceedings/icsgea/2021/3263/0",
"title": "2021 6th International Conference on Smart Grid and Electrical Automation (ICSGEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaie/2021/2492/0/249200a252",
"title": "Design and development of wechat applet for Qi Culture Communication",
"doi": null,
"abstractUrl": "/proceedings-article/icaie/2021/249200a252/1wV1FaUbpsI",
"parentPublication": {
"id": "proceedings/icaie/2021/2492/0",
"title": "2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaie/2021/2492/0/249200a298",
"title": "Research on Exploration on Curriculum Reform of Western Music History Based on WeChat Platform",
"doi": null,
"abstractUrl": "/proceedings-article/icaie/2021/249200a298/1wV1L8I6HXW",
"parentPublication": {
"id": "proceedings/icaie/2021/2492/0",
"title": "2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aemcse/2021/1596/0/159600a997",
"title": "Research and Design of Automatic Parking System Based on Wechat Applet",
"doi": null,
"abstractUrl": "/proceedings-article/aemcse/2021/159600a997/1wcdgeF7yXm",
"parentPublication": {
"id": "proceedings/aemcse/2021/1596/0",
"title": "2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaa/2021/3730/0/373000a735",
"title": "Teacher-Student Learning Community Based on WeChat",
"doi": null,
"abstractUrl": "/proceedings-article/icaa/2021/373000a735/1zL1MKB8jok",
"parentPublication": {
"id": "proceedings/icaa/2021/3730/0",
"title": "2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.