id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
SCOPUS_ID:78651098688 | A 3D-shape retrieval system to improve the text retrieval | This paper describes a 3D model retrieval system based on Google 3D Warehouse, which consists of 3D models in .skp format. Because of the quickly expanding of the 3D models on the web and the insistent demands of 3D models in virtual reality, virtual scene modeling and 3D animation, there is an increasing need for a se... | [
"Information Retrieval"
] | [
24
] |
SCOPUS_ID:0032958476 | A 4-year investigation into phonetic inventory development in young cochlear implant users | Phonetic inventories of 9 children with profoundly impaired hearing who used the 22-electrode cochlear implant (Cochlear Limited) were monitored before implantation and during the first 4 years of implant use. All children were 5 years old or younger at the time of implant. Spontaneous speech samples were collected at ... | [
"Phonetics",
"Syntactic Text Processing"
] | [
64,
15
] |
SCOPUS_ID:85037163649 | A 500 million word POS-tagged icelandic corpus | The new POS-tagged Icelandic corpus of the Leipzig Corpora Collection is an extensive resource for the analysis of the Icelandic language. As it contains a large share of all Web documents hosted under the.is top-level domain, it is especially valuable for investigations on modern Icelandic and non-standard language va... | [
"Tagging",
"Syntactic Text Processing"
] | [
63,
15
] |
SCOPUS_ID:85055564668 | A 5W1H based annotation scheme for semantic role labeling of English tweets | Semantic Role Labeling (SRL) is a well researched area of Natural Language Processing. State-of-the-art lexical resources have been developed for SRL on formal texts that involve a tedious annotation scheme and require linguistic expertise. The difficulties increase manifold when such complex annotation scheme is appli... | [
"Semantic Parsing",
"Semantic Text Processing"
] | [
40,
72
] |
http://arxiv.org/abs/2110.01258v1 | A Aelf-supervised Tibetan-chinese Vocabulary Alignment Method Based On Adversarial Learning | Tibetan is a low-resource language. In order to alleviate the shortage of parallel corpus between Tibetan and Chinese, this paper uses two monolingual corpora and a small number of seed dictionaries to learn the semi-supervised method with seed dictionaries and self-supervised adversarial training method through the si... | [
"Low-Resource NLP",
"Robustness in NLP",
"Responsible & Trustworthy NLP"
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80,
58,
4
] |
SCOPUS_ID:84900508576 | A BBS opinion leader mining algorithm based on topic model | The BBS opinion leader mining is the primary goal of public opinion control and the existing mining algorithm can not find out the topic-specific opinion leaders. This paper presents a BBS opinion leader mining algorithm based on topic model (TOLM). The study first preprocesses the post titles based on their publicatio... | [
"Topic Modeling",
"Information Extraction & Text Mining",
"Sentiment Analysis"
] | [
9,
3,
78
] |
SCOPUS_ID:84874800985 | A BDI dialogue agent for social support: Specification and evaluation method | An important task for empathic agents is to provide social support, that is, to help people increase their well-being and decrease the perceived burden of their problems. The contributions of this paper are 1) the specification of speech acts for a social support dialogue agent, and 2) an evaluation method for this age... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85131231441 | A BERT BASED JOINT LEARNING MODEL WITH FEATURE GATED MECHANISM FOR SPOKEN LANGUAGE UNDERSTANDING | Intent detection (ID) and slot filling (SF) are two major tasks for spoken language understanding (SLU). Recent joint learning approaches consider the relationship between intent detection and slot filling, which leverage the shared knowledge across two tasks to benefit each other. However, most existing methods do not... | [
"Language Models",
"Semantic Text Processing",
"Semantic Parsing",
"Intent Recognition",
"Sentiment Analysis"
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52,
72,
40,
79,
78
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SCOPUS_ID:85115137488 | A BERT Based Approach for Arabic POS Tagging | Large pre-trained language models, such as BERT, have recently achieved state-of-the-art performance in different natural language processing tasks. However, BERT based models in Arabic language are less abundant than in other languages. This paper aims to design a grammatical tagging system for texts in Arabic languag... | [
"Language Models",
"Tagging",
"Semantic Text Processing",
"Syntactic Text Processing"
] | [
52,
63,
72,
15
] |
http://arxiv.org/abs/1901.08634v3 | A BERT Baseline for the Natural Questions | This technical note describes a new baseline for the Natural Questions. Our model is based on BERT and reduces the gap between the model F1 scores reported in the original dataset paper and the human upper bound by 30% and 50% relative for the long and short answer tasks respectively. This baseline has been submitted t... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85145612050 | A BERT Framework to Sentiment Analysis of Tweets | Sentiment analysis has been widely used in microblogging sites such as Twitter in recent decades, where millions of users express their opinions and thoughts because of its short and simple manner of expression. Several studies reveal the state of sentiment which does not express sentiment based on the user context bec... | [
"Language Models",
"Semantic Text Processing",
"Sentiment Analysis"
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52,
72,
78
] |
SCOPUS_ID:85132015024 | A BERT Model-Based Sentiment Analysis on COVID-19 Tweets | In the past few decades, the growth of data on the Internet has increased significantly, and even today, tons of data get generated with each passing day. The World Wide Web has become a great source of e-learning, sharing ideas, and interchanging school of thoughts and views. Internet community sites like Twitter, Fac... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
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3
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SCOPUS_ID:85125999983 | A BERT and Topic Model Based Approach to reviews Requirements Analysis | With the rise of mobile applications, user reviews are an important avenue of user feedback in which users may mention different issues in using the software. For example, unresponsiveness, low-level privacy, etc. In order to extract effective requirement information and problematic feedback from these huge user review... | [
"Language Models",
"Topic Modeling",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
9,
72,
3
] |
SCOPUS_ID:85107799787 | A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts | The emergence and rapid progress of the Internet have brought ever-increasing impact on financial domain. How to rapidly and accurately mine the key information from the massive negative financial texts has become one of the key issues for investors and decision Rakers. Aiming at the issue, we propose a sentiment analy... | [
"Language Models",
"Semantic Text Processing",
"Named Entity Recognition",
"Sentiment Analysis",
"Information Extraction & Text Mining"
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52,
72,
34,
78,
3
] |
SCOPUS_ID:85127180477 | A BERT based dual-channel explainable text emotion recognition system | In this paper, a novel dual-channel system for multi-class text emotion recognition has been proposed, and a novel technique to explain its training & predictions has been developed. The architecture of the proposed system contains the embedding module, dual-channel module, emotion classification module, and explainabi... | [
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Information Retrieval",
"Sentiment Analysis",
"Representation Learning",
"Explainability & Interpretability in NLP",
"Text Clustering",
"Emotion Analysis",
"Text Classification",
"Responsible & Trustworthy NL... | [
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SCOPUS_ID:85133025073 | A BERT-Based Approach for Multilingual Discourse Connective Detection | In this paper, we report on our experiments towards multilingual discourse connective (or DC) identification and show how language specific BERT models seem to be sufficient even with little task-specific training data. While some languages have large corpora with human annotated DCs, most languages are low in such res... | [
"Discourse & Pragmatics",
"Language Models",
"Semantic Text Processing",
"Multilinguality"
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71,
52,
72,
0
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SCOPUS_ID:85149113734 | A BERT-Based Artificial Intelligence to Analyze Free-Text Clinical Notes for Binary Classification in Papillary Thyroid Carcinoma Recurrence | Patient information in free text form exists in medical information systems. Before the successes of the natural language processing models, it had costed resources to refine unstructured information into neat information formats for training artificial intelligence models. Here, we applied the bidirectional encoder re... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
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52,
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SCOPUS_ID:85133590359 | A BERT-Based Aspect-Level Sentiment Analysis Algorithm for Cross-Domain Text | Cross-domain text sentiment analysis is a text sentiment classification task that uses the existing source domain annotation data to assist the target domain, which can not only reduce the workload of new domain data annotation, but also significantly improve the utilization of source domain annotation resources. In or... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
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52,
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23,
78,
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SCOPUS_ID:85129993541 | A BERT-Based Automatic Scoring Model of Korean Language Learners' Essay | This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners’ writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used f... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85122020760 | A BERT-Based Generation Model to Transform Medical Texts to SQL Queries for Electronic Medical Records: Model Development and Validation | Background: Electronic medical records (EMRs) are usually stored in relational databases that require SQL queries to retrieve information of interest. Effectively completing such queries can be a challenging task for medical experts due to the barriers in expertise. Existing text-to-SQL generation studies have not been... | [
"Language Models",
"Programming Languages in NLP",
"Semantic Text Processing",
"Representation Learning",
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"Code Generation",
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52,
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47,
44,
74
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SCOPUS_ID:85132965819 | A BERT-Based Model for Question Answering on Construction Incident Reports | Construction sites are among the most hazardous workplaces. To reduce accidents, it is required to identify risky situations beforehand, and to describe which countermeasures to put in place. In this paper, we investigate possible techniques to support the identification of risky activities and potential hazards associ... | [
"Language Models",
"Natural Language Interfaces",
"Semantic Text Processing",
"Question Answering"
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52,
11,
72,
27
] |
SCOPUS_ID:85100611845 | A BERT-Based Semantic Matching Ranker for Open-Domain Question Answering | Open-domain question answering (QA) is a hot topic in recent years. Previous work has shown that an effective ranker can improve the overall QA performance by denoising irrelevant context. There are also some recent works leveraged BERT pre-trained model to tackle with open-domain QA tasks, and achieved significant imp... | [
"Language Models",
"Semantic Text Processing",
"Question Answering",
"Semantic Similarity",
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52,
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53,
11
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SCOPUS_ID:85076696813 | A BERT-Based Transfer Learning Approach for Hate Speech Detection in Online Social Media | Generated hateful and toxic content by a portion of users in social media is a rising phenomenon that motivated researchers to dedicate substantial efforts to the challenging direction of hateful content identification. We not only need an efficient automatic hate speech detection model based on advanced machine learni... | [
"Language Models",
"Semantic Text Processing",
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
52,
72,
17,
4
] |
SCOPUS_ID:85111442441 | A BERT-Bi-LSTM-Based Knowledge Graph Question Answering Method | With the development of knowledge graph, the research of question answering methods based on knowledge graph has gradually become a hot spot. However, in the current mainstream question answering methods, there is insufficient mining of the semantic information of question sentences, resulting in poor entity recognitio... | [
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Structured Data in NLP",
"Question Answering",
"Knowledge Representation",
"Named Entity Recognition",
"Natural Language Interfaces",
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52,
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74
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SCOPUS_ID:85082138835 | A BERT-BiLSTM-CRF model for Chinese electronic medical records named entity recognition | Named entity recognition is a fundamental task in natural language processing and many studies have done about it in recent decades. Previous word representation methods represent words as a single vector of multiple dimensions, which ignore the ambiguity of the character in Chinese. To solve this problem, we apply a B... | [
"Language Models",
"Named Entity Recognition",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
34,
72,
3
] |
SCOPUS_ID:85093870821 | A BERT-based Approach with Relation-aware Attention for Knowledge Base Question Answering | Knowledge Base Question Answering (KBQA), which uses the facts in the knowledge base (KB) to answer natural language questions, has received extensive attention in recent years. The existing works mainly focus on the modeling method and neglect the relations between questions and KB facts, which might restrict the furt... | [
"Language Models",
"Semantic Text Processing",
"Question Answering",
"Natural Language Interfaces",
"Knowledge Representation"
] | [
52,
72,
27,
11,
18
] |
http://arxiv.org/abs/2211.01954v1 | A BERT-based Deep Learning Approach for Reputation Analysis in Social Media | Social media has become an essential part of the modern lifestyle, with its usage being highly prevalent. This has resulted in unprecedented amounts of data generated from users in social media, such as users' attitudes, opinions, interests, purchases, and activities across various aspects of their lives. Therefore, in... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
http://arxiv.org/abs/2010.05384v1 | A BERT-based Distractor Generation Scheme with Multi-tasking and Negative Answer Training Strategies | In this paper, we investigate the following two limitations for the existing distractor generation (DG) methods. First, the quality of the existing DG methods are still far from practical use. There is still room for DG quality improvement. Second, the existing DG designs are mainly for single distractor generation. Ho... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
4
] |
http://arxiv.org/abs/2011.02378v1 | A BERT-based Dual Embedding Model for Chinese Idiom Prediction | Chinese idioms are special fixed phrases usually derived from ancient stories, whose meanings are oftentimes highly idiomatic and non-compositional. The Chinese idiom prediction task is to select the correct idiom from a set of candidate idioms given a context with a blank. We propose a BERT-based dual embedding model ... | [
"Language Models",
"Semantic Text Processing",
"Representation Learning"
] | [
52,
72,
12
] |
SCOPUS_ID:85114964457 | A BERT-based End-to-End Model for Chinese Document-level Event Extraction | Document-level event extraction aims at discovering event mentions and extracting events which contain event arguments and their roles from texts. This paper proposes an end-to-end model for closed-domain based on BERT. We introduce the embedding of event type and entity nodes to the subsequent layer for event argument... | [
"Language Models",
"Semantic Text Processing",
"Representation Learning",
"Event Extraction",
"Information Extraction & Text Mining"
] | [
52,
72,
12,
31,
3
] |
SCOPUS_ID:85099597607 | A BERT-based Hierarchical Model for Vietnamese Aspect Based Sentiment Analysis | Aspect based sentiment analysis (ABSA) is the task of identifying sentiment polarity towards specific entities and their aspects mentioned in customers' reviews. This paper presents a new and effective hierarchical model using the pre-trained language model, Bidirectional Encoder Representations from Transformers (BERT... | [
"Language Models",
"Semantic Text Processing",
"Polarity Analysis",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis"
] | [
52,
72,
33,
23,
78
] |
SCOPUS_ID:85137904470 | A BERT-based Idiom Detection Model | Idioms are figures of speech that contradict the principle of compositionality. This disposition of idioms can misdirect Natural Language Processing (NLP) techniques, which mostly focus on the literal meaning of terms. In this paper, we propose a novel idiom detection model that distinguishes between literal and idioma... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Multimodality"
] | [
52,
72,
70,
74
] |
SCOPUS_ID:85140077157 | A BERT-based Language Modeling Framework | Deep learning has brought considerable changes and created a new paradigm in many research areas, including computer vision, speech processing, and natural language processing. In the context of language modeling, recurrent-based language models and word embedding methods have been pivotal studies in the past decade. R... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Multimodality"
] | [
52,
72,
70,
74
] |
SCOPUS_ID:85137179072 | A BERT-based Text Sentiment Classification Algorithm through Web Data | In order to analyze the sentiment tendency of public opinion, this paper conducts a textual sentiment classification research through web data. In the research, this paper uses the BERT (Bidirectional Encoder Representation from Transformers) model to replace the commonly used word2vec model as a text vectorization too... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
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52,
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24,
3
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SCOPUS_ID:85071179765 | A BERT-based approach for automatic humor detection and scoring | In this paper we report our participation in the 2019 HAHA task where a corpus of crowd-annotated tweets is provided and required to tell if a tweet is a joke or not and predict a funniness score value for a tweet. Our approach utilizes BERT, a multi-layer bidirectional transformer encoder which can help learn deep bi-... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Commonsense Reasoning",
"Reasoning",
"Text Classification",
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52,
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24,
62,
8,
36,
3
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SCOPUS_ID:85134556431 | A BERT-based ensemble learning approach for the BioCreative VII challenges: full-text chemical identification and multi-label classification in PubMed articles | In this research, we explored various state-of-the-art biomedical-specific pre-trained Bidirectional Encoder Representations from Transformers (BERT) models for the National Library of Medicine - Chemistry (NLM CHEM) and LitCovid tracks in the BioCreative VII Challenge, and propose a BERT-based ensemble learning approa... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:85089591944 | A BERT-based ensemble model for chinese news topic prediction | With the rapid development of big data mining technology in the Chinese commercial field, the news topic prediction becomes increasingly important. Since the accuracy of Chinese news topic classification can directly affect the personalized recommendation effect of the Chinese news system and then affect business profi... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:85131918728 | A BERT-based multi-semantic learning model with aspect-aware enhancement for aspect polarity classification | Aspect-Based Sentiment Classification (ABSA), predicting the sentimental tendency towards given aspects, is an important branch in natural language understanding. However, in the existing deep learning models for ABSA, there is a contradiction between the fine sentiment analysis and the small amount of corpus. To solve... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Polarity Analysis",
"Sentiment Analysis",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
33,
78,
36,
3
] |
SCOPUS_ID:85099884804 | A BERT-based named entity recognition in chinese electronic medical record | Named entity recognition, aiming at identifying and classifying named entity mentioned in the structured or unstructured text, is a fundamental subtask for information extraction in natural language processing (NLP). With the development of electronic medical records, obtaining the key and effective information in elec... | [
"Language Models",
"Named Entity Recognition",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
34,
72,
3
] |
SCOPUS_ID:85113848708 | A BERT-based system for multi-topic labeling of Arabic content | Text classification (or categorization) is one of the most common natural language processing (NLP) tasks. It is very useful to simplify the management of a large volume of textual data by assigning each text to one or more categories. This operation is challenging when it is a multi-label classification. For Arabic te... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
24,
3
] |
SCOPUS_ID:85141198696 | A BIBLIOMETRIC AND TOPIC MODELING OVERVIEW OF KAJIAN MALAYSIA BETWEEN 2011 AND 2020: A RESEARCH NOTE | Kajian Malaysia, published by Penerbit Universiti Sains Malaysia, is an interdisciplinary journal which provides a forum for a broad range of social sciences and humanities research. This research note presents a bibliometric review of the articles published in the journal Kajian Malaysia between 2011 and 2020. The pur... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85123986946 | A BIBLIOMETRIC APPROACH TO SUPPORT REDEFINING MANAGEMENT OF TECHNOLOGY FOR THE POST-DIGITAL WORLD | Management of Technology (MoT) has evolved since its inception in the 1980s and definitions from the 1990s. However, the field's definition may not be keeping up with the ever-increasing changes in our world. This paper implements bibliometrics, through natural language processing and topic modelling, of published lite... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
http://arxiv.org/abs/1908.08674v1 | A BLSTM Network for Printed Bengali OCR System with High Accuracy | This paper presents a printed Bengali and English text OCR system developed by us using a single hidden BLSTM-CTC architecture having 128 units. Here, we did not use any peephole connection and dropout in the BLSTM, which helped us in getting better accuracy. This architecture was trained by 47,720 text lines that incl... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Multimodality"
] | [
20,
52,
72,
74
] |
SCOPUS_ID:0012130276 | A BOOTSTRAP TECHNIQUE FOR BUILDING DOMAIN-DEPENDENT LANGUAGE MODELS | In this paper, we propose a new bootstrap technique to build domain-dependent language models. We assume that a seed corpus consisting of a small amount of data relevant to the new domain is available, which is used to build a reference language model. We also assume the availability of an external corpus, consisting o... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:84901745856 | A BP neural network text categorization method optimized by an improved genetic algorithm | The back propagation(BP) neural network is widely used for text categorization and could achieve high performance. However, the greatest disadvantage of this network is its long training time. The genetic algorithm is often used to generate useful solutions for optimization. In this paper we combined the genetic algori... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:80051910758 | A BST-based approach to dictionary structure for Chinese word segmentation | This paper firstly analyzes current Chinese word segmentation methods, and then bases on word dictionary segmentation and binary search tree (BST) proposing a way to organize the dictionary which focuses on reducing comparison times in order to increase the segmentation speed. After that, a practical demo is used to il... | [
"Text Segmentation",
"Syntactic Text Processing"
] | [
21,
15
] |
SCOPUS_ID:85120079173 | A Background Knowledge Revising and Incorporating Dialogue Model | Currently, dialogue systems have attracted increasing research interest. In particular, background knowledge is incorporated to improve the performance of dialogue systems. Existing dialogue systems mostly assume that the background knowledge is correct and comprehensive. However, low-quality background knowledge is co... | [
"Language Models",
"Natural Language Interfaces",
"Semantic Text Processing",
"Dialogue Systems & Conversational Agents"
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52,
11,
72,
38
] |
SCOPUS_ID:85030166830 | A Badge of Honor?: How The New York Times discredits President Trump’s fake news accusations | News organizations in many Western democracies face decreasing trust amid fake news accusations. In this situation, news organizations risk losing their license to operate and need to defend their legitimacy. This study analyzes how The New York Times (NYT) discredits fake news accusations, which are prominently expres... | [
"Semantic Text Processing",
"Discourse & Pragmatics",
"Ethical NLP",
"Reasoning",
"Fact & Claim Verification",
"Responsible & Trustworthy NLP"
] | [
72,
71,
17,
8,
46,
4
] |
http://arxiv.org/abs/2109.08232v1 | A Bag of Tricks for Dialogue Summarization | Dialogue summarization comes with its own peculiar challenges as opposed to news or scientific articles summarization. In this work, we explore four different challenges of the task: handling and differentiating parts of the dialogue belonging to multiple speakers, negation understanding, reasoning about the situation,... | [
"Summarization",
"Natural Language Interfaces",
"Text Generation",
"Dialogue Systems & Conversational Agents",
"Information Extraction & Text Mining"
] | [
30,
11,
47,
38,
3
] |
SCOPUS_ID:85059967366 | A Bag-of-Phonetic-Codes Modelfor Cyber-Bullying Detection in Twitter | Social networking sites such as Twitter, Facebook, MySpace, Instagram are emerging as a strong medium of communication these days. These have become a part and parcel of daily life. People can express their thoughts and activities among their social circle with brings them closer to their community. However this freedo... | [
"Phonetics",
"Syntactic Text Processing",
"Sentiment Analysis"
] | [
64,
15,
78
] |
SCOPUS_ID:85075500006 | A Bag of Constrained Visual Words Model for Image Representation | We propose a bag of constrained visual words model for image representation. Each image under this model is considered to be an aggregation of patches. SURF features are used to describe each patch. Two sets of constraints, namely, the must-link and the cannot-link, are developed for each patch in a completely unsuperv... | [
"Visual Data in NLP",
"Information Extraction & Text Mining",
"Semantic Text Processing",
"Representation Learning",
"Text Clustering",
"Information Retrieval",
"Multimodality"
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20,
3,
72,
12,
29,
24,
74
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SCOPUS_ID:85055970663 | A Bakhtinian take on languaging in a dual language immersion classroom | Language brings a classroom to life and crafts the teaching and learning space. Sociocultural theories of language acquisition and learning focus on the role of language as a mediator for development. While research on languaging and translanguaging practices in English medium and multilingual classrooms is on the rise... | [
"Multilinguality",
"Linguistic Theories",
"Speech & Audio in NLP",
"Linguistics & Cognitive NLP",
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0,
57,
70,
48,
74
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http://arxiv.org/abs/2205.04086v1 | A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank | We show that the choice of pretraining languages affects downstream cross-lingual transfer for BERT-based models. We inspect zero-shot performance in balanced data conditions to mitigate data size confounds, classifying pretraining languages that improve downstream performance as donors, and languages that are improved... | [
"Multilinguality",
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Cross-Lingual Transfer",
"Responsible & Trustworthy NLP"
] | [
0,
52,
80,
72,
19,
4
] |
SCOPUS_ID:85077992328 | A Bangla Spell Checking Technique to Facilitate Error Correction in Text Entry Environment | Spell checker is a common tool used in different text entry techniques for error free writing. Recent advances in spell checking techniques in different languages significantly decreases word and sentence level typos from writing text. But developing an optimized spell checker in Bangla language is still a great resear... | [
"Text Error Correction",
"Syntactic Text Processing"
] | [
26,
15
] |
SCOPUS_ID:85081661138 | A Bangla Word Sense Disambiguation Technique using Minimum Edit Distance Algorithm and Cosine Distance | In Natural Language Processing, Morphology known as the most decisive part. It can be more difficult when there are several meanings for only one word. Ambiguous word is a word which has those several meanings. The human brain can easily identify these ambiguities but for machines, it is very complicated to detect. Wor... | [
"Semantic Text Processing",
"Word Sense Disambiguation"
] | [
72,
65
] |
SCOPUS_ID:85077205506 | A Barrage sentiment analysis scheme based on expression and tone | Most of existing methods do not consider the influence of expression and tone on barrage sentiment analysis. This decreases the effect and accuracy of barrage sentiment analysis. Therefore, we propose a barrage sentiment analysis scheme based on expression and tone. First, we propose a new sentiment dictionary based on... | [
"Sentiment Analysis"
] | [
78
] |
http://arxiv.org/abs/2008.10648v2 | A Baseline Analysis for Podcast Abstractive Summarization | Podcast summary, an important factor affecting end-users' listening decisions, has often been considered a critical feature in podcast recommendation systems, as well as many downstream applications. Existing abstractive summarization approaches are mainly built on fine-tuned models on professionally edited texts such ... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
http://arxiv.org/abs/1907.12437v1 | A Baseline Neural Machine Translation System for Indian Languages | We present a simple, yet effective, Neural Machine Translation system for Indian languages. We demonstrate the feasibility for multiple language pairs, and establish a strong baseline for further research. | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:67649435512 | A Basic Parallel Process as a Parallel Pushdown Automaton | We investigate the set of basic parallel processes, recursively defined by action prefix, interleaving, 0 and 1. Different from literature, we use the constants 0 and 1 standing for unsuccessful and successful termination in order to stay closer to the analogies in automata theory. We prove that any basic parallel proc... | [
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
48,
57
] |
http://arxiv.org/abs/1708.05997v2 | A Batch Noise Contrastive Estimation Approach for Training Large Vocabulary Language Models | Training large vocabulary Neural Network Language Models (NNLMs) is a difficult task due to the explicit requirement of the output layer normalization, which typically involves the evaluation of the full softmax function over the complete vocabulary. This paper proposes a Batch Noise Contrastive Estimation (B-NCE) appr... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:84911871232 | A Battleground of identity: Racial formation and the african american discourse on interracial marriage | This article utilizes a sample of letters to the editor from African American newspapers to investigate racial identity formation. Drawing on an analysis of 234 letters, published predominantly between 1925 and 1965, I examine howAfrican American writers discussed black-white intermarriage. Writers used the issue of in... | [
"Discourse & Pragmatics",
"Semantic Text Processing"
] | [
71,
72
] |
SCOPUS_ID:85109430198 | A Baybayin word recognition system | Baybayin is a pre-Hispanic Philippine writing system used in Luzon island. With the effort in reintroducing the script, in 2018, the Committee on Basic Education and Culture of the Philippine Congress approved House Bill 1022 or the ‘’National Writing System Act,” which declares the Baybayin script as the Philippines’ ... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85122566072 | A Bayesian CNN-LSTM Model for Sentiment Analysis in Massive Open Online Courses MOOCs | Massive Open Online Courses (MOOCs) are increasingly used by learners to acquire knowledge and develop new skills. MOOCs provide a trove of data that can be leveraged to better assist learners, including behavioral data from built-in collaborative tools such as discussion boards and course wikis. Data tracing social in... | [
"Language Models",
"Semantic Text Processing",
"Sentiment Analysis"
] | [
52,
72,
78
] |
SCOPUS_ID:84968876693 | A Bayesian Classification Approach Using Class-Specific Features for Text Categorization | In this paper, we present a Bayesian classification approach for automatic text categorization using class-specific features. Unlike conventional text categorization approaches, our proposed method selects a specific feature subset for each class. To apply these class-specific features for classification, we follow Bag... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
http://arxiv.org/abs/0907.0785v1 | A Bayesian Model for Discovering Typological Implications | A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as ``if objects come after verbs, then adjectives come after nouns.'' Such implications are typically discovered by painstaking hand analysis over a small sample of ... | [
"Typology",
"Syntactic Text Processing",
"Multilinguality"
] | [
45,
15,
0
] |
http://arxiv.org/abs/1506.04334v2 | A Bayesian Model for Generative Transition-based Dependency Parsing | We propose a simple, scalable, fully generative model for transition-based dependency parsing with high accuracy. The model, parameterized by Hierarchical Pitman-Yor Processes, overcomes the limitations of previous generative models by allowing fast and accurate inference. We propose an efficient decoding algorithm bas... | [
"Syntactic Parsing",
"Syntactic Text Processing"
] | [
28,
15
] |
http://arxiv.org/abs/1603.01514v1 | A Bayesian Model of Multilingual Unsupervised Semantic Role Induction | We propose a Bayesian model of unsupervised semantic role induction in multiple languages, and use it to explore the usefulness of parallel corpora for this task. Our joint Bayesian model consists of individual models for each language plus additional latent variables that capture alignments between roles across langua... | [
"Multilinguality",
"Low-Resource NLP",
"Semantic Text Processing",
"Semantic Parsing",
"Responsible & Trustworthy NLP"
] | [
0,
80,
72,
40,
4
] |
http://arxiv.org/abs/1310.3099v2 | A Bayesian Network View on Acoustic Model-Based Techniques for Robust Speech Recognition | This article provides a unifying Bayesian network view on various approaches for acoustic model adaptation, missing feature, and uncertainty decoding that are well-known in the literature of robust automatic speech recognition. The representatives of these classes can often be deduced from a Bayesian network that exten... | [
"Speech & Audio in NLP",
"Robustness in NLP",
"Text Generation",
"Responsible & Trustworthy NLP",
"Speech Recognition",
"Multimodality"
] | [
70,
58,
47,
4,
10,
74
] |
SCOPUS_ID:85019013527 | A Bayesian Race Model for Recognition Memory | Many psychological models use the idea of a trace, which represents a change in a person’s cognitive state that arises as a result of processing a given stimulus. These models assume that a trace is always laid down when a stimulus is processed. In addition, some of these models explain how response times (RTs) and res... | [
"Cognitive Modeling",
"Linguistics & Cognitive NLP"
] | [
2,
48
] |
SCOPUS_ID:84971513897 | A Bayesian Sampling Method for Product Feature Extraction from Large-Scale Textual Data | The authors of this work propose an algorithm that determines optimal search keyword combinations for querying online product data sources in order to minimize identification errors during the product feature extraction process. Data-driven product design methodologies based on acquiring and mining online product-featu... | [
"Information Extraction & Text Mining"
] | [
3
] |
SCOPUS_ID:85144435663 | A Bayesian Topic Model for Human-Evaluated Interpretability | One desideratum of topic modeling is to produce interpretable topics. Given a cluster of document-tokens comprising a topic, we can order the topic by counting each word. It is natural to think that each topic could easily be labeled by looking at the words with the highest word count. However, this is not always the c... | [
"Low-Resource NLP",
"Topic Modeling",
"Explainability & Interpretability in NLP",
"Responsible & Trustworthy NLP",
"Information Extraction & Text Mining"
] | [
80,
9,
81,
4,
3
] |
SCOPUS_ID:85028462788 | A Bayesian approach for semantic search based on DAG-shaped ontologies | Semantic search has a great potentiality in helping users to make choices, since it appears to outperform traditional keyword-based approaches. This paper presents an ontology-based semantic search method, referred to as influential SemSim (i-SemSim), which relies on the Bayesian probabilistic approach for weighting th... | [
"Semantic Search",
"Knowledge Representation",
"Semantic Text Processing",
"Information Retrieval"
] | [
41,
18,
72,
24
] |
SCOPUS_ID:85006944225 | A Bayesian approach forweighted ontologies and semantic search | Semantic similarity search is one of the most promising methods for improving the performance of retrieva systems. This paper presents a new probabilistic method for ontology weighting based on a Bayesian approach In particular, this work addresses the semantic search method SemSim for evaluating the similarity amon a ... | [
"Semantic Search",
"Knowledge Representation",
"Semantic Text Processing",
"Information Retrieval"
] | [
41,
18,
72,
24
] |
SCOPUS_ID:84977103368 | A Bayesian approach to classify the music scores on the basis of the music style | This article presents a new version of the algorithm proposed by Della Ventura (12th TELE-INFO International Conference on Recent Researches in Telecommunications, and Informatics, 2013, [1]) to classify the musical scores. Score classification means an automatic process of assignment of the specific score to a certain... | [
"Text Classification",
"Speech & Audio in NLP",
"Multimodality",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
70,
74,
24,
3
] |
SCOPUS_ID:67651097685 | A Bayesian approach to intention-based response generation | The statistical approach to natural language generation of overgeneration-and-ranking suffers from expensive overgeneration. This article reports the findings of response classification experiment in the new approach of intention-based classification-and- ranking. Possible responses are deliberately chosen from a dialo... | [
"Dialogue Response Generation",
"Text Classification",
"Natural Language Interfaces",
"Text Generation",
"Dialogue Systems & Conversational Agents",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
14,
36,
11,
47,
38,
24,
3
] |
SCOPUS_ID:84867191524 | A Bayesian approach to semantic composition for spoken language interpretation | This paper introduces a stochastic interpretation process for composing semantic structures. This process, dedicated to spoken language interpretation, allows to derive semantic frame structures directly from word and basic concept sequences representing the users' utterances. First a two-step rule-based process has be... | [
"Explainability & Interpretability in NLP",
"Natural Language Interfaces",
"Responsible & Trustworthy NLP",
"Dialogue Systems & Conversational Agents"
] | [
81,
11,
4,
38
] |
SCOPUS_ID:85097057119 | A Bayesian brain model of adaptive behavior: An application to the Wisconsin Card Sorting Task | Adaptive behavior emerges through a dynamic interaction between cognitive agents and changing environmental demands. The investigation of information processing underlying adaptive behavior relies on controlled experimental settings in which individuals are asked to accomplish demanding tasks whereby a hidden regularit... | [
"Cognitive Modeling",
"Linguistics & Cognitive NLP"
] | [
2,
48
] |
SCOPUS_ID:85016946262 | A Bayesian classifiers based combination model for automatic text classification | Text classification deals with allocating a text document to a predetermined class. Generally, this involves learning about a class from representations of documents belonging to that class. In this paper, we propose a classifier combination that uses a Multinomial Naïve Bayesian (MNB) classifier along with Bayesian Ne... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85095410236 | A Bayesian end-to-end model with estimated uncertainties for simple question answering over knowledge bases | Existing methods for question answering over knowledge bases (KBQA) ignore the consideration of the model prediction uncertainties. We argue that estimating such uncertainties is crucial for the reliability and interpretability of KBQA systems. Therefore, we propose a novel end-to-end KBQA model based on Bayesian Neura... | [
"Natural Language Interfaces",
"Knowledge Representation",
"Semantic Text Processing",
"Question Answering"
] | [
11,
18,
72,
27
] |
SCOPUS_ID:84857369324 | A Bayesian feature selection paradigm for text classification | The automated classification of texts into predefined categories has witnessed a booming interest, due to the increased availability of documents in digital form and the ensuing need to organize them. An important problem for text classification is feature selection, whose goals are to improve classification effectiven... | [
"Information Extraction & Text Mining",
"Green & Sustainable NLP",
"Text Classification",
"Information Retrieval",
"Responsible & Trustworthy NLP"
] | [
3,
68,
36,
24,
4
] |
SCOPUS_ID:84874529222 | A Bayesian framework for simultaneously modeling neural and behavioral data | Scientists who study cognition infer underlying processes either by observing behavior (e.g., response times, percentage correct) or by observing neural activity (e.g., the BOLD response). These two types of observations have traditionally supported two separate lines of study. The first is led by cognitive modelers, w... | [
"Cognitive Modeling",
"Linguistics & Cognitive NLP"
] | [
2,
48
] |
SCOPUS_ID:67349278780 | A Bayesian framework for word segmentation: Exploring the effects of context | Since the experiments of Saffran et al. [Saffran, J., Aslin, R., & Newport, E. (1996). Statistical learning in 8-month-old infants. Science, 274, 1926-1928], there has been a great deal of interest in the question of how statistical regularities in the speech stream might be used by infants to begin to identify individ... | [
"Text Segmentation",
"Speech & Audio in NLP",
"Syntactic Text Processing",
"Multimodality"
] | [
21,
70,
15,
74
] |
SCOPUS_ID:84963589419 | A Bayesian hierarchical model for comparing average F1 scores | In multi-class text classification, the performance (effectiveness) of a classifier is usually measured by micro-averaged and macro-averaged F1 scores. However, the scores themselves do not tell us how reliable they are in terms of forecasting the classifier's future performance on unseen data. In this paper, we propos... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:72449200175 | A Bayesian learning approach to promoting diversity in ranking for biomedical information retrieval | In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in the biomedical domain. First, the re-ranking model computes the maximum posterior probability of the hidden property corresponding to each ret... | [
"Passage Retrieval",
"Information Retrieval"
] | [
66,
24
] |
SCOPUS_ID:84877760378 | A Bayesian model for learning SCFGs with discontiguous rules | We describe a nonparametric model and corresponding inference algorithm for learning Synchronous Context Free Grammar derivations for parallel text. The model employs a Pitman-Yor Process prior which uses a novel base distribution over synchronous grammar rules. Through both synthetic grammar induction and statistical ... | [
"Text Error Correction",
"Machine Translation",
"Syntactic Text Processing",
"Text Generation",
"Multilinguality"
] | [
26,
51,
15,
47,
0
] |
https://aclanthology.org//2010.iwslt-papers.7/ | A Bayesian model of bilingual segmentation for transliteration | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] | |
SCOPUS_ID:77952922710 | A Bayesian model of syntax-directed tree to string grammar induction | Tree based translation models are a compelling means of integrating linguistic information into machine translation. Syntax can inform lexical selection and reordering choices and thereby improve translation quality. Research to date has focussed primarily on decoding with such models, but less on the difficult problem... | [
"Text Error Correction",
"Machine Translation",
"Syntactic Text Processing",
"Text Generation",
"Multilinguality"
] | [
26,
51,
15,
47,
0
] |
SCOPUS_ID:84866015784 | A Bayesian modeling approach to multi-dimensional sentiment distributions prediction | Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions pr... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Sentiment Analysis"
] | [
3,
24,
36,
78
] |
SCOPUS_ID:15944425469 | A Bayesian network coding scheme for annotating biomedical information presented to genetic counseling clients | We developed a Bayesian network coding scheme for annotating biomedical content in layperson-oriented clinical genetics documents. The coding scheme supports the representation of probabilistic and causal relationships among concepts in this domain, at a high enough level of abstraction to capture commonalities among g... | [
"Text Generation"
] | [
47
] |
SCOPUS_ID:84937812818 | A Bayesian non-linear method for feature selection in machine translation quality estimation | We perform a systematic analysis of the effectiveness of features for the problem of predicting the quality of machine translation (MT) at the sentence level. Starting from a comprehensive feature set, we apply a technique based on Gaussian processes, a Bayesian non-linear learning method, to automatically identify fea... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:84925276643 | A Bayesian nonparametric topic model for user interest modeling | Web users display their preferences implicitly by a sequence of pages they navigated. Web recommendation systems use methods to extract useful knowledge about user interests from such data. We propose a Bayesian nonparametric approach to the problem of modeling user interests in recommender systems using implicit feedb... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85065234797 | A Bayesian race model for response times under cyclic stimulus discriminability | Response time (RT) data from psychology experiments are often used to validate theories of how the brain processes information and how long it takes a person to make a decision. When an RT results from a task involving two or more possible responses, the cognitive process that determines the RT may be modeled as the fi... | [
"Cognitive Modeling",
"Linguistics & Cognitive NLP"
] | [
2,
48
] |
SCOPUS_ID:84971612146 | A Bayesian recommender model for user rating and review profiling | Intuitively, not only do ratings include abundant information for learning user preferences, but also reviews accompanied by ratings. However, most existing recommender systems take rating scores for granted and discard the wealth of information in accompanying reviews. In this paper, in order to exploit user profiles'... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:84883267393 | A Bayesian topic model for spam filtering | Spam is one of the major problems of today's Internet because it brings financial damage to companies and annoys individual users. Among those approaches developed to detect spam, the content-based machine learning algorithms are important and popular. However, these algorithms are trained using statistical representat... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
http://arxiv.org/abs/2012.10251v1 | A Benchmark Arabic Dataset for Commonsense Explanation | Language comprehension and commonsense knowledge validation by machines are challenging tasks that are still under researched and evaluated for Arabic text. In this paper, we present a benchmark Arabic dataset for commonsense explanation. The dataset consists of Arabic sentences that does not make sense along with thre... | [
"Commonsense Reasoning",
"Explainability & Interpretability in NLP",
"Reasoning",
"Responsible & Trustworthy NLP"
] | [
62,
81,
8,
4
] |
http://arxiv.org/abs/2202.02013v2 | A Benchmark Corpus for the Detection of Automatically Generated Text in Academic Publications | Automatic text generation based on neural language models has achieved performance levels that make the generated text almost indistinguishable from those written by humans. Despite the value that text generation can have in various applications, it can also be employed for malicious tasks. The diffusion of such practi... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Text Generation",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
52,
72,
36,
47,
24,
3
] |
https://aclanthology.org//W14-2109/ | A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics | [
"Argument Mining",
"Reasoning"
] | [
60,
8
] | |
http://arxiv.org/abs/1909.04251v1 | A Benchmark Dataset for Learning to Intervene in Online Hate Speech | Countering online hate speech is a critical yet challenging task, but one which can be aided by the use of Natural Language Processing (NLP) techniques. Previous research has primarily focused on the development of NLP methods to automatically and effectively detect online hate speech while disregarding further action ... | [
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
17,
4
] |
SCOPUS_ID:85144420853 | A Benchmark Dataset for Multi-Level Complexity-Controllable Machine Translation | This paper introduces a new benchmark test dataset for multi-level complexity-controllable machine translation (MLCC-MT), which is an MT that controls the output complexity at more than two levels. In previous studies, MLCC-MT models have been evaluated on a test dataset automatically generated from the Newsela corpus,... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
http://arxiv.org/abs/2210.12314v1 | A Benchmark Study of Contrastive Learning for Arabic Social Meaning | Contrastive learning (CL) brought significant progress to various NLP tasks. Despite this progress, CL has not been applied to Arabic NLP to date. Nor is it clear how much benefits it could bring to particular classes of tasks such as those involved in Arabic social meaning (e.g., sentiment analysis, dialect identifica... | [
"Language Models",
"Semantic Text Processing",
"Representation Learning"
] | [
52,
72,
12
] |
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