id stringlengths 20 52 | title stringlengths 3 459 | abstract stringlengths 0 12.3k | classification_labels list | numerical_classification_labels list |
|---|---|---|---|---|
SCOPUS_ID:85131410750 | A Local context focus learning model for joint multi-task using syntactic dependency relative distance | Aspect-based sentiment analysis (ABSA) is a significant task in natural language processing. Although many ABSA systems have been proposed, the correlation between the aspect’s sentiment polarity and local context semantic information was not a point of focus. Moreover, aspect term extraction and aspect sentiment class... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Information Retrieval",
"Term Extraction",
"Syntactic Text Processing",
"Aspect-based Sentiment Analysis",
"Sentiment Analysis",
"Responsible & Trustworthy NLP",
"Text Classification",
"Information Extraction & Text Mining"
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52,
80,
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1,
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23,
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36,
3
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SCOPUS_ID:85081345898 | A Location Independent Machine Learning Approach for Early Fake News Detection | The spread of fake news on the internet is presenting increasing threats to national security, with the potential to incite public unrest and violence. However, detecting fake news is challenging as they are intentionally written to mislead. Some current methods cannot detect fake news early and require external inform... | [
"Reasoning",
"Fact & Claim Verification",
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
8,
46,
17,
4
] |
SCOPUS_ID:85137146707 | A Logic Aware Neural Generation Method for Explainable Data-to-text | The most notable neural data-to-text approaches generate natural language from structural data relying on the surface form of the structural content, which ignores the underlying logical correlation between the input data and the target text. Moreover, identifying such logical associations and explaining them in natura... | [
"Explainability & Interpretability in NLP",
"Data-to-Text Generation",
"Text Generation",
"Responsible & Trustworthy NLP"
] | [
81,
16,
47,
4
] |
http://arxiv.org/abs/2110.03323v3 | A Logic-Based Framework for Natural Language Inference in Dutch | We present a framework for deriving inference relations between Dutch sentence pairs. The proposed framework relies on logic-based reasoning to produce inspectable proofs leading up to inference labels; its judgements are therefore transparent and formally verifiable. At its core, the system is powered by two ${\lambda... | [
"Reasoning",
"Textual Inference",
"Syntactic Text Processing"
] | [
8,
22,
15
] |
SCOPUS_ID:85065962278 | A Logic-Based Question Answering System for Cultural Heritage | Question Answering (QA) systems attempt to find direct answers to user questions posed in natural language. This work presents a QA system for the closed domain of Cultural Heritage. Our solution gradually transforms input questions into queries that are executed on a CIDOC-compliant ontological knowledge base. Questio... | [
"Natural Language Interfaces",
"Question Answering"
] | [
11,
27
] |
http://arxiv.org/abs/1310.4938v1 | A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge | We present the architecture and the evaluation of a new system for recognizing textual entailment (RTE). In RTE we want to identify automatically the type of a logical relation between two input texts. In particular, we are interested in proving the existence of an entailment between them. We conceive our system as a m... | [
"Semantic Text Processing",
"Syntactic Text Processing",
"Knowledge Representation",
"Reasoning",
"Textual Inference"
] | [
72,
15,
18,
8,
22
] |
SCOPUS_ID:85143765239 | A Logical Conceptualization of Knowledge on the Notion of Language Communication | The main objective of the paper is to provide a conceptual apparatus of a general logical theory of language communication. The aim of the paper is to outline a formal-logical theory of language in which the concepts of the phenomenon of language communication and language communication in general are defined and some ... | [
"Linguistics & Cognitive NLP",
"Linguistic Theories"
] | [
48,
57
] |
SCOPUS_ID:1542379838 | A Logico-mathematic, Structural Methodology: Part I, the Analysis and Validation of Sub-literal (S<inf>ub</inf>L<inf>it</inf>) Language and Cognition | In this first of three papers, a novel cognitive and psycho-linguistic non metric or non quantitative methodology developed for the analysis and validation of unconscious cognition and meaning in ostensibly literal verbal narratives is presented. Unconscious referents are reconceptualized as sub-literal (SubLit) refere... | [
"Reasoning",
"Numerical Reasoning",
"Psycholinguistics",
"Linguistics & Cognitive NLP"
] | [
8,
5,
77,
48
] |
SCOPUS_ID:85084278034 | A Logistic Regression Approach for Generating Movies Reputation Based on Mining User Reviews | The paper aims to present an approach for generating a single reputation value towards a target movie based on mining movie reviews and their attached ratings with the use of Logistic Regression classifier and Latent Semantic Indexing (LSI) method. The contribution of the paper is fourfold. First, we apply Logistic Reg... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Sentiment Analysis"
] | [
3,
24,
36,
78
] |
SCOPUS_ID:85101083795 | A Long Short-Term Memory (LSTM) Model for Business Sentiment Analysis Based on Recurrent Neural Network | Business sentiment analysis (BSA) is one of the significant and popular topics of natural language processing. It is one kind of sentiment analysis techniques for business purpose. Different categories of sentiment analysis techniques like lexicon-based techniques and different types of machine learning algorithms are ... | [
"Language Models",
"Semantic Text Processing",
"Sentiment Analysis"
] | [
52,
72,
78
] |
SCOPUS_ID:85127481481 | A Long-Text Classification Method of Chinese News Based on BERT and CNN | Text Classification is an important research area in natural language processing (NLP) that has received a considerable amount of scholarly attention in recent years. However, real Chinese online news is characterized by long text, a large amount of information and complex structure, which also reduces the accuracy of ... | [
"Language Models",
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
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52,
72,
36,
12,
24,
3
] |
SCOPUS_ID:85106551999 | A Longitudinal Study of Spanish Language Growth and Loss in Young Spanish-English Bilingual Children | This longitudinal study examined trajectories of Spanish language growth and loss in 34 Spanish-English bilingual children attending an English immersion school. Narrative retell language samples were collected in Spanish across 3 years using wordless, picture storybooks. Digital audio recordings were transcribed, code... | [
"Code-Switching",
"Multilinguality"
] | [
7,
0
] |
SCOPUS_ID:85137330497 | A Look at the Sociointerational Discourse Analysis Between Caregivers and Institutionalized Older Women in Bathing Care | Based on Ethnomethodology and Conversational Analysis, and anchored in the Sociointerational Discourse Analysis, this article sought to analyze the speeches of health professionals and their association with stigmas related to institutionalized older women at the time of bathing care. Data were collected using field no... | [
"Discourse & Pragmatics",
"Semantic Text Processing",
"Ethical NLP",
"Responsible & Trustworthy NLP"
] | [
71,
72,
17,
4
] |
http://arxiv.org/abs/1908.08917v1 | A Lost Croatian Cybernetic Machine Translation Program | We are exploring the historical significance of research in the field of machine translation conducted by Bulcsu Laszlo, Croatian linguist, who was a pioneer in machine translation in Yugoslavia during the 1950s. We are focused on two important seminal papers written by members of his research group from 1959 and 1962,... | [
"Programming Languages in NLP",
"Machine Translation",
"Multimodality",
"Text Generation",
"Multilinguality"
] | [
55,
51,
74,
47,
0
] |
http://arxiv.org/abs/1705.10754v1 | A Low Dimensionality Representation for Language Variety Identification | Language variety identification aims at labelling texts in a native language (e.g. Spanish, Portuguese, English) with its specific variation (e.g. Argentina, Chile, Mexico, Peru, Spain; Brazil, Portugal; UK, US). In this work we propose a low dimensionality representation (LDR) to address this task with five different ... | [
"Semantic Text Processing",
"Representation Learning"
] | [
72,
12
] |
SCOPUS_ID:85077256437 | A Low Effort Approach to Structured CNN Design Using PCA | Deep learning models hold state of the art performance in many fields, yet their design is still based on heuristics or grid search methods that often result in overparametrized networks. This work proposes a method to analyze a trained network and deduce an optimized, compressed architecture that preserves accuracy wh... | [
"Responsible & Trustworthy NLP",
"Green & Sustainable NLP"
] | [
4,
68
] |
SCOPUS_ID:85135064820 | A Low-Cost, Controllable and Interpretable Task-Oriented Chatbot: With Real-World After-Sale Services as Example | Though widely used in industry, traditional task-oriented dialogue systems suffer from three bottlenecks: (i) difficult ontology construction (e.g., intents and slots); (ii) poor controllability and interpretability; (iii) annotation-hungry. In this paper, we propose to represent utterance with a simpler concept named ... | [
"Explainability & Interpretability in NLP",
"Natural Language Interfaces",
"Responsible & Trustworthy NLP",
"Dialogue Systems & Conversational Agents"
] | [
81,
11,
4,
38
] |
SCOPUS_ID:85131591413 | A Low-Latency Streaming On-Device Automatic Speech Recognition System Using a CNN Acoustic Model on FPGA and a Language Model on Smartphone | This paper presents a low-latency streaming on-device automatic speech recognition system for inference. It consists of a hardware acoustic model implemented in a field-programmable gate array, coupled with a software language model running on a smartphone. The smartphone works as the master of the automatic speech rec... | [
"Language Models",
"Programming Languages in NLP",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Text Generation",
"Speech Recognition",
"Multimodality"
] | [
52,
55,
72,
70,
47,
10,
74
] |
SCOPUS_ID:85107366405 | A Lucrative Model for Identifying Potential Adverse Effects from Biomedical Texts by Augmenting BERT and ELMo | This study copes with extracting adverse effects (AEs) from biomedical texts. An adverse effect is a noxious, unintended, and undesired effect caused by the administration of an external entity such as medication, dietary supplement, radiotherapy, and others. A binary classifier is proposed to filter out irrelevant tex... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:85145880055 | A META HEURISTIC MULTI-VIEW DATA ANALYSIS OVER UNCONDITIONAL LABELED MATERIAL: AN INTELLIGENCE OCMHAMCV | Artificial intelligence has been provided powerful research attributes like data mining and clustering for reducing bigdata functioning. Clustering in multi-labeled categorical analysis gives huge amount of relevant data that explains evaluation and portrayal of qualities as trending notion. A wide range of scenarios, ... | [
"Information Extraction & Text Mining",
"Summarization",
"Text Generation",
"Text Clustering",
"Responsible & Trustworthy NLP",
"Green & Sustainable NLP"
] | [
3,
30,
47,
29,
4,
68
] |
SCOPUS_ID:85122575584 | A METHOD TO IMPROVE EXACT MATCHING RESULTS IN COMPRESSED TEXT USING PARALLEL WAVELET TREE | The process of searching on the World Wide Web (WWW.is increasing regularly, and users around the world also use it regularly. In WWW the size of the text corpus is constantly increasing at an exponential rate, so we need an efficient indexing algorithm that reduces both space and time during the search process. This pa... | [
"Tagging",
"Indexing",
"Information Retrieval",
"Syntactic Text Processing"
] | [
63,
69,
24,
15
] |
SCOPUS_ID:85055487445 | A MIML-LSTM neural network for integrated fine-grained event forecasting | Societal event forecasting plays a significant role in crisis warning and emergency management. Most traditional prediction methods focus on predicting whether specific events would happen or not. However, the results of these methods are not always informative for the policy makers due to excessive frequency, lack of ... | [
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining"
] | [
52,
72,
3
] |
SCOPUS_ID:85009195509 | A MISSING-WORD TEST COMPARISON OF HUMAN AND STATISTICAL LANGUAGE MODEL PERFORMANCE | A suite of missing-word tests based on text extracts selected randomly from two different text corpora provided a metric which was used in an evaluation of human performance, an evaluation of language model performance and a cross-comparison of the performances. The effects of providing different sizes of context for t... | [
"Language Models",
"Semantic Text Processing"
] | [
52,
72
] |
SCOPUS_ID:84957830652 | A MODULAR ARCHITECTURE SUPPORTING MULTIPLE HYPOTHESES FOR CONVERSION OF TEXT TO PHONETIC AND LINGUISTIC ENTITIES | In this communication we devise a distributed modular scheme for organizing the different types of knowledge needed in the first phase of text-to-speech conversion, namely the conversion of the input text to a symbolic notation, representing phonetic transcription together with syntactic, semantic and pragmatic informa... | [
"Phonetics",
"Speech & Audio in NLP",
"Syntactic Text Processing",
"Multimodality"
] | [
64,
70,
15,
74
] |
https://aclanthology.org//2007.mtsummit-papers.61/ | A MT system from Turkmen to Turkish employing finite state and statistical methods | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] | |
SCOPUS_ID:85131265568 | A MULTI DOMAIN KNOWLEDGE ENHANCED MATCHING NETWORK FOR RESPONSE SELECTION IN RETRIEVAL-BASED DIALOGUE SYSTEMS | Building a human-machine conversational agent is a core problem in Artificial Intelligence, where knowledge has to be integrated into the model effectively. In this paper, we propose a Multi Domain Knowledge Enhanced Matching Network (MDKEMN) to build retrieval-based dialogue systems that could leverage both explicit k... | [
"Semantic Text Processing",
"Structured Data in NLP",
"Knowledge Representation",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Information Retrieval",
"Multimodality"
] | [
72,
50,
18,
11,
38,
24,
74
] |
SCOPUS_ID:0038791970 | A MULTILINGUAL TEXT PROCESSING ENGINE FOR THE PAPAGENO TEXT-TO-SPEECH SYNTHESIS SYSTEM | Automatic synthesis of speech from arbitrary text requires two basic operations: linguistic analysis of input text and speech waveform generation. The achieved quality of the second stage very much depends on the reliability and richness of information generated in the first stage. In this paper we discuss possibilitie... | [
"Multimodality",
"Speech & Audio in NLP",
"Multilinguality"
] | [
74,
70,
0
] |
SCOPUS_ID:85103551874 | A Machine Learning Analysis of the Recent Environmental and Resource Economics Literature | We use topic modeling to study research articles in environmental and resource economics journals in the period 2000–2019. Topic modeling based on machine learning allows us to identify and track latent topics in the literature over time and across journals, and further to study the role of different journals in differ... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85062225018 | A Machine Learning Approach for Graph-Based Page Segmentation | We propose a new approach for segmenting a document image into its page components (e.g. text, graphics and tables). Our approach consists of two main steps. In the first step, a set of scores corresponding to the output of a convolutional neural network, one for each of the possible page component categories, is assig... | [
"Structured Data in NLP",
"Text Classification",
"Multimodality",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
50,
36,
74,
24,
3
] |
SCOPUS_ID:85075690608 | A Machine Learning Approach for Hot Topic Detection in News | We explore the related problems of topic detection within the stream of news sources collected by newspapers aggregators. In this paper, we focus on evaluating the effectiveness of the collaboration between preprocessing techniques and document clustering techniques and propose to use Pearson product-moment correlation... | [
"Information Extraction & Text Mining",
"Text Clustering"
] | [
3,
29
] |
SCOPUS_ID:85131927856 | A Machine Learning Approach for Multiclass Sentiment Analysis of Twitter Data: A Review | Sentiment analysis or opinion mining is a prominent and most demanding research topic in today’s world. The main idea behind this research topic is to recognize the user’s opinions and emotions towards the aspect of service or product via a text basis. Sentiment analysis involves mining text, lexicon construction, extr... | [
"Opinion Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
49,
36,
78,
24,
3
] |
SCOPUS_ID:85131915998 | A Machine Learning Approach for Sentiment Analysis of Book Reviews in Bangla Language | With the advent of technology, Sentiment polarity detection has recently piqued the interest of NLP researchers. Sentiment analysis determines the profound meaning of an article. Due to COVID-19 pandemic, online shopping is the safest way of shopping. Moreover, there are product quality and service issues. Our target i... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85103742695 | A Machine Learning Approach for the Classification of Methamphetamine Dealers on Twitter in Thailand. | This research presents a method to classify messages from Twitter (tweet) related to Methamphetamine. The messages are classified into three classes: normal, seller, buyer. The models presented in this research are Multinomial Naive Bayes, Multi-Class LSTM, and Hierarchical LSTM. Model training uses a balanced and imba... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Syntactic Text Processing",
"Text Segmentation",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
15,
21,
36,
3
] |
SCOPUS_ID:85113863360 | A Machine Learning Approach to Analyze Fashion Styles from Large Collections of Online Customer Reviews | Social media and online reviews have changed customer behavior when buying fashion products online. Online customer reviews also provide opportunities for businesses to deliver improved customer experiences. This study aims to develop fashion style models, based on online customer reviews from e-commerce systems to ana... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85132773969 | A Machine Learning Approach to Analyze Mental Health from Reddit Posts | Reddit is a platform with a heavy focus on its community forums and hence is comparatively unique from other social media platforms. It is divided into sub-Reddits, resulting in distinct topic-specific communities. The convenience of expressing thoughts, a flexibility of describing emotions, inter-operability of using ... | [
"Responsible & Trustworthy NLP",
"Ethical NLP",
"Information Extraction & Text Mining"
] | [
4,
17,
3
] |
http://arxiv.org/abs/2211.07705v1 | A Machine Learning Approach to Classifying Construction Cost Documents into the International Construction Measurement Standard | We introduce the first automated models for classifying natural language descriptions provided in cost documents called "Bills of Quantities" (BoQs) popular in the infrastructure construction industry, into the International Construction Measurement Standard (ICMS). The models we deployed and systematically evaluated f... | [
"Semantic Text Processing",
"Text Classification",
"Representation Learning",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
72,
36,
12,
24,
3
] |
http://arxiv.org/abs/1903.06765v1 | A Machine Learning Approach to Comment Toxicity Classification | Now-a-days, derogatory comments are often made by one another, not only in offline environment but also immensely in online environments like social networking websites and online communities. So, an Identification combined with Prevention System in all social networking websites and applications, including all the com... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85028022723 | A Machine Learning Approach to Evaluating Translation Quality | We explored supervised machine learning (ML) techniques to understand and predict the adequacy and fluency of English-Spanish machine translation. Five experiments were conducted using three classifiers in Weka, an open-source ML tool. We found that the highest performance was achieved by applying a dimensionality redu... | [
"Machine Translation",
"Information Extraction & Text Mining",
"Text Classification",
"Text Generation",
"Information Retrieval",
"Multilinguality"
] | [
51,
3,
36,
47,
24,
0
] |
SCOPUS_ID:85136872428 | A Machine Learning Approach to Model HRI Research Trends in 20102021 | The present study collects a large amount of HRI-related research studies and analyzes the research trends from 2010 to 2021. Through the topic modeling technique, our developed ML model is able to retrieve the dominant research factors. The preliminary results reveal five important topics, handover, privacy, robot tut... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85127955130 | A Machine Learning Approach to POS Tagging Case study: Amazighe language | The development of automatic processing tools for amazighe language is hampered by the lack of resources for these. In this sense, one of the main objectives of the work reported in this article is to provide this language with a morphosyntactic annotated corpus and a better precision system for morphosyntaxic labeling... | [
"Tagging",
"Syntactic Text Processing"
] | [
63,
15
] |
http://arxiv.org/abs/1810.06639v4 | A Machine Learning Approach to Persian Text Readability Assessment Using a Crowdsourced Dataset | An automated approach to text readability assessment is essential to a language and can be a powerful tool for improving the understandability of texts written and published in that language. However, the Persian language, which is spoken by over 110 million speakers, lacks such a system. Unlike other languages such as... | [
"Semantic Text Processing",
"Text Complexity"
] | [
72,
42
] |
SCOPUS_ID:85113361236 | A Machine Learning Approach to Sentiment Analysis on Web Based Feedback | The advent of this new era of technology has brought forward new and convenient ways to express views and opinions. This is a major factor for the vast influx of data that we experience every day. People have found out new ways to communicate their feelings and emotions to others through written texts sent over the Int... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85127489679 | A Machine Learning Approach to Track COVID-19 Pandemic using Sentiment Analysis | Coronavirus disease or COVID-19 is one of the most frightening and infectious diseases of the twenty-first century. Since the outbreak of COVID-19 in Wuhan, China, numerous researches are conducted in this sector. At the preliminary stage, there was not sufficient numeric data for research but when we consider the text... | [
"Information Extraction & Text Mining",
"Information Retrieval",
"Text Classification",
"Sentiment Analysis"
] | [
3,
24,
36,
78
] |
http://arxiv.org/abs/cmp-lg/9607022v1 | A Machine Learning Approach to the Classification of Dialogue Utterances | The purpose of this paper is to present a method for automatic classification of dialogue utterances and the results of applying that method to a corpus. Superficial features of a set of training utterances (which we will call cues) are taken as the basis for finding relevant utterance classes and for extracting rules ... | [
"Text Classification",
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
11,
38,
24,
3
] |
SCOPUS_ID:85051127172 | A Machine Learning Based Approach for Opinion Mining on Social Network Data | Micro-blogging has been widely used for voicing out opinions in the public domain. One such website, Twitter is a point of attraction for researchers in the areas such as prediction of electoral events, movie box office, stock market, consumer brands etc. In our paper, we focus on using Twitter, for the task of opinion... | [
"Opinion Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
49,
36,
78,
24,
3
] |
SCOPUS_ID:85106415770 | A Machine Learning Based Framework for Enterprise Document Classification | Enterprise Content Management (ECM) systems store large amounts of documents that have to be conveniently labelled for easy managed and searching. The classification rules behind the labelling process are informal and tend to change that complicates the labelling even more. We propose a machine learning based document ... | [
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
36,
3
] |
SCOPUS_ID:85062596565 | A Machine Learning Based Natural Language Question and Answering System for Healthcare Data Search using Complex Queries | Number of use cases in healthcare are well suited as Big Data applications. In healthcare, large volumes of data are coming in and stored as unstructured big data or as structured data in relational database. In any case, Big Data is coming to embrace SQL as a common tool for querying. Developing a question and answeri... | [
"Information Retrieval",
"Question Answering",
"Natural Language Interfaces",
"Text Classification",
"Information Extraction & Text Mining"
] | [
24,
27,
11,
36,
3
] |
SCOPUS_ID:85128216022 | A Machine Learning Based Sameness Recognition Method for Power System Management Information | State Grid Corporation's power construction project information comes from multiple regions and different scale power construction sub-project, and there are missing fillings and irregularities, which makes supervision difficult, and brings difficulties in project acceptance and management. Based on the random forest a... | [
"Text Classification",
"Syntactic Text Processing",
"Text Segmentation",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
36,
15,
21,
24,
3
] |
SCOPUS_ID:85063769591 | A Machine Learning Based Sentiment Analysis by Selecting Features for Predicting Customer Reviews | Nowadays people can express their opinions and views publicly which can be favour and/or against any service, issue, product, event, or policy. With the rapid advancement of internet, people can share their feedback on the web in huge numbers. This large number of reviews for individuals can be crucial to improve their... | [
"Opinion Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
49,
36,
78,
24,
3
] |
SCOPUS_ID:85141733119 | A Machine Learning Method for Customer Sentiment Analysis on Social Media | Customer Data analysis is a significant part of different ventures utilizing figuring applications, for example, E-business and online shopping. Enormous information is utilized for advancing items which gives better availability among retailers and customers. These days, individuals consistently utilize online advance... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85140882832 | A Machine Learning Method for Prediction of Stock Market Using Real-Time Twitter Data | Finances represent one of the key requirements to perform any useful activity for humanity. Financial markets, e.g., stock markets, forex, and mercantile exchanges, etc., provide the opportunity to anyone to invest and generate finances. However, to reap maximum benefits from these financial markets, effective decision... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85069507352 | A Machine Learning Model for Average Fuel Consumption in Heavy Vehicles | This paper advocates a data summarization approach based on distance rather than the traditional time period when developing individualized machine learning models for fuel consumption. This approach is used in conjunction with seven predictors derived from vehicle speed and road grade to produce a highly predictive ne... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
http://arxiv.org/abs/2109.09014v1 | A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches | Computational methods to model political bias in social media involve several challenges due to heterogeneity, high-dimensional, multiple modalities, and the scale of the data. Political bias in social media has been studied in multiple viewpoints like media bias, political ideology, echo chambers, and controversies us... | [
"Multimodality",
"Ethical NLP",
"Speech & Audio in NLP",
"Responsible & Trustworthy NLP"
] | [
74,
17,
70,
4
] |
SCOPUS_ID:84991619945 | A Machine Learning approach for classification of sentence polarity | Opinion Mining is the process used to determine the attitude/opinion/emotion expressed by a person about a particular topic. Analyzing opinions is an integral part for making decisions. In the era of web, if a person wants to buy a product, he will look into the reviews and comments given by the experienced users in we... | [
"Opinion Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
49,
36,
78,
24,
3
] |
SCOPUS_ID:85145438542 | A Machine Learning based Approach to Identify User Interests from Social Data | Social media platforms like Twitter, Facebook, Instagram, etc., are considered a common source of extracting information about individuals, such as their needs, interests, and opinions. Our major contribution in this paper is to identify user interests and desires related to the fashion industry in Pakistan. Since peop... | [
"Language Models",
"Semantic Text Processing",
"Text Clustering",
"Sentiment Analysis",
"Information Extraction & Text Mining"
] | [
52,
72,
29,
78,
3
] |
http://arxiv.org/abs/2211.14321v1 | A Machine Learning, Natural Language Processing Analysis of Youth Perspectives: Key Trends and Focus Areas for Sustainable Youth Development Policies | Investing in children and youth is a critical step towards inclusive, equitable, and sustainable development for current and future generations. Several international agendas for accomplishing common global goals emphasize the need for active youth participation and engagement for sustainable development. The 2030 Agen... | [
"Green & Sustainable NLP",
"Responsible & Trustworthy NLP",
"Sentiment Analysis"
] | [
68,
4,
78
] |
SCOPUS_ID:85148025762 | A Machine Learning-Based Mobile Chatbot for Crop Farmers | Agriculture remains the basis of the country’s economy, providing the main source of livelihood for most citizenry such as food, employment, income and foreign exchange as well as raw materials for the manufacturing sectors. Despite the great need for economic advancement in crop farming, agriculture seems to be limite... | [
"Natural Language Interfaces",
"Knowledge Representation",
"Semantic Text Processing",
"Dialogue Systems & Conversational Agents"
] | [
11,
18,
72,
38
] |
SCOPUS_ID:85139208454 | A Machine Learning-Based Technique with Intelligent WordNet Lemmatize for Twitter Sentiment Analysis | Laterally with the birth of the Internet, the fast growth of mobile strategies has democratised content production owing to the widespread usage of social media, resulting in a detonation of short informal writings. Twitter is microblogging short text and social networking services, with posted millions of quick messag... | [
"Sentiment Analysis"
] | [
78
] |
SCOPUS_ID:85125967115 | A Machine Learning-Based Tool for Exploring Covid-19 Scientific Literature | The advent of the COVID-19 pandemic caused by the Sars-CoV2 virus has caused serious damage in different areas. This has prompted thousands of researchers from different disciplines (biology, medicine, artificial intelligence, economics, etc.) to publish a very large number of scientific articles in a very short period... | [
"Topic Modeling",
"Information Extraction & Text Mining",
"Text Clustering"
] | [
9,
3,
29
] |
SCOPUS_ID:85148467292 | A Machine Learning-Sentiment Analysis on Monkeypox Outbreak: An Extensive Dataset to Show the Polarity of Public Opinion From Twitter Tweets | Research on sentiment analysis has proven to be very useful in public health, particularly in analyzing infectious diseases. As the world recovers from the onslaught of the COVID-19 pandemic, concerns are rising that another pandemic, known as monkeypox, might hit the world again. Monkeypox is an infectious disease rep... | [
"Polarity Analysis",
"Sentiment Analysis"
] | [
33,
78
] |
SCOPUS_ID:85061379799 | A Machine Reading Comprehension-Based Approach for Featured Snippet Extraction | The extraction of featured snippet can be considered as the problem of Question Answering (QA). This paper presents a featured snippet extraction system by employing a technique of machine reading comprehension (MRC). Specifically, we first analyze the characteristics of questions with different types and their corresp... | [
"Information Extraction & Text Mining",
"Question Answering",
"Natural Language Interfaces",
"Reasoning",
"Machine Reading Comprehension"
] | [
3,
27,
11,
8,
37
] |
SCOPUS_ID:85135766291 | A Machine Speech Chain Approach for Dynamically Adaptive Lombard TTS in Static and Dynamic Noise Environments | Recent end-to-end text-to-speech synthesis (TTS) systems have successfully synthesized high-quality speech. However, TTS speech intelligibility degrades in noisy environments because most of these systems were not designed to handle noisy environments. Several works attempted to address this problem by using offline fi... | [
"Language Models",
"Semantic Text Processing",
"Speech & Audio in NLP",
"Multimodality"
] | [
52,
72,
70,
74
] |
https://aclanthology.org//2018.iwslt-1.6/ | A Machine Translation Approach for Modernizing Historical Documents Using Backtranslation | Human language evolves with the passage of time. This makes historical documents to be hard to comprehend by contemporary people and, thus, limits their accessibility to scholars specialized in the time period in which a certain document was written. Modernization aims at breaking this language barrier and increase the... | [
"Multilinguality",
"Machine Translation",
"Ethical NLP",
"Text Generation",
"Responsible & Trustworthy NLP"
] | [
0,
51,
17,
47,
4
] |
SCOPUS_ID:85130093774 | A Machine Translation Framework Based on Neural Network Deep Learning: from Semantics to Feature Analysis | This paper uses an encoder-decoder framework based on semantic to feature analysis to construct a neural machine translation model, let the machine automatically perform feature learning, transform corpus data into word vectors in a distributed representation, and use neural networks to implement source language and Di... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
https://aclanthology.org//2022.eamt-1.54/ | A Machine Translation-Powered Chatbot for Public Administration | This paper is about a multilingual chatbot developed for public administration within the CEF funded project ENRICH4ALL. We argue for multi-lingual chatbots empowered through MT and discuss the integration of the CEF eTranslation service in a chatbot solution. | [
"Machine Translation",
"Natural Language Interfaces",
"Text Generation",
"Dialogue Systems & Conversational Agents",
"Multilinguality"
] | [
51,
11,
47,
38,
0
] |
SCOPUS_ID:85146119140 | A Machine Transliteration Tool Between Uzbek Alphabets | Machine transliteration, as defined in this paper, is a process of automatically transforming written script of words from a source alphabet into words of another target alphabet within the same language, while preserving their meaning, as well as pronunciation. The main goal of this paper is to present a machine trans... | [
"Low-Resource NLP",
"Responsible & Trustworthy NLP"
] | [
80,
4
] |
SCOPUS_ID:85029170521 | A Machine learning Filter for Relation Extraction | The TAC KBP English slot filling track is an evaluation campaign that targets the extraction of 41 pre-identified relations related to specific named entities. In this work, we present a machine learning filter whose aim is to enhance the precision of relation extractors while minimizing the impact on recall. Our appro... | [
"Semantic Text Processing",
"Information Retrieval",
"Relation Extraction",
"Semantic Parsing",
"Text Classification",
"Information Extraction & Text Mining"
] | [
72,
24,
75,
40,
36,
3
] |
SCOPUS_ID:85135831949 | A Machine-Learning Analysis of the Impacts of the COVID-19 Pandemic on Small Business Owners and Implications for Canadian Government Policy Response | This study applies a machine-learning technique to a dataset of 38,000 textual comments from Canadian small business owners on the impacts of coronavirus disease 2019 (COVID-19). Topic modelling revealed seven topics covering the short- and longer-term impacts of the pandemic, government relief programs and loan eligib... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:84965053749 | A Macroscopic Analysis of News Content in Twitter | Previous literature has considered the relevance of Twitter to journalism, for example as a tool for reporters to collect information and for organizations to disseminate news to the public. We consider the reciprocal perspective, carrying out a survey of news media-related content within Twitter. Using a random sample... | [
"Topic Modeling",
"Information Extraction & Text Mining"
] | [
9,
3
] |
SCOPUS_ID:85039951960 | A Malay named entity recognition using conditional random fields | Currently, unstructured textual data analysis has attracted researchers' interest because it offers valuable information into many fields such as business, education, political, healthcare, crime prevention and other. Various sources are accessible that contain unstructured textual data such as online documents, Facebo... | [
"Named Entity Recognition",
"Information Extraction & Text Mining"
] | [
34,
3
] |
SCOPUS_ID:84979683319 | A Malay text corpus analysis for sentence compression using pattern-growth method | A text summary extracts serves as a condensed representation of a written input source where important and salient information is kept. However, the condensed representation itself suffer in lack of semantic and coherence if the summary was produced in verbatim using the input itself. Sentence Compression is a techniqu... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:85015877295 | A Malay text summarizer using pattern-growth method with sentence compression rules | A text summary is a condensed representation of text where salient information is extracted with the purpose to ease users' readability. However, if the summary was extracted 'verbatim' from its source, the sentence may contain inessential information along with salient information that may effect on the overall cohere... | [
"Summarization",
"Text Generation",
"Information Extraction & Text Mining"
] | [
30,
47,
3
] |
SCOPUS_ID:73849094644 | A Malayalam OCR system using column-stochastic image matrix approach | Indian languages especially South Indian languages have several distinct characteristics that are exploited for the development of a robust optical character recognition system (OCR). This paper addresses the problem of segmentation of printed Malayalam characters, a fairly complex task, along with their characterizati... | [
"Visual Data in NLP",
"Multimodality"
] | [
20,
74
] |
SCOPUS_ID:85027871374 | A Mandarin phonetic-symbol communication aid developed on tablet computers for children with high-functioning autism | In this study, a Mandarin phonetic symbol communication aid named as the Zhuyin communication board was developed for children with high-functioning autism. The Zhuyin communication board can be operated on tablet computers to assist autistic children with expressing their thoughts. By using this aid, autistic children... | [
"Phonetics",
"Structured Data in NLP",
"Syntactic Text Processing",
"Multimodality"
] | [
64,
50,
15,
74
] |
SCOPUS_ID:84949501731 | A Mandarin spoken dialogue system with limited portability | In the new generation human-computer interaction technology, spoken dialog system based on content is the key issue. This paper describes the status of our spoken dialogue system for tour information retrieval-GUIDE, whose lexicon consists of 2000 Words and WER is 5.7%. Different from AT1S application, tour information... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85128791884 | A Manifold Learning Method to Passage Retrieval for Open-Domain Question Answering | Passage retriever plays an important role for obtaining answers in open-domain textual question answering system, which selects candidate contexts from a large collection of documents and feed to the machine reader. Traditional defacto methods usually construct sparse vectors to match the rules of co-occurrence of word... | [
"Passage Retrieval",
"Natural Language Interfaces",
"Question Answering",
"Information Retrieval"
] | [
66,
11,
27,
24
] |
http://arxiv.org/abs/1805.05542v1 | A Manually Annotated Chinese Corpus for Non-task-oriented Dialogue Systems | This paper presents a large-scale corpus for non-task-oriented dialogue response selection, which contains over 27K distinct prompts more than 82K responses collected from social media. To annotate this corpus, we define a 5-grade rating scheme: bad, mediocre, acceptable, good, and excellent, according to the relevance... | [
"Natural Language Interfaces",
"Dialogue Systems & Conversational Agents"
] | [
11,
38
] |
SCOPUS_ID:85141185410 | A MapReduce Clustering Approach for Sentiment Analysis Using Big Data | The modern era of organizations are generating huge amount of data by digitalizing their way of promoting services and products. The companies trying to know what customers are saying in terms of products through reviews in social media analytics constitutes a prime factor to enhance the success of big data era. Howeve... | [
"Information Extraction & Text Mining",
"Sentiment Analysis",
"Text Clustering"
] | [
3,
78,
29
] |
SCOPUS_ID:85111153622 | A MapReduce Improved ID3 Decision Tree for Classifying Twitter Data | In this contribution, we introduce an innovative classification approach for opinion mining. We have used the feature extractor Fast Text to detect and capture the given tweets’ relevant data efficiently. Then, we have applied the feature selector Information Gain to reduce the dimensionality of the high feature. Final... | [
"Opinion Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
49,
36,
78,
24,
3
] |
SCOPUS_ID:85104238923 | A MapReduce Opinion Mining for COVID-19-Related Tweets Classification Using Enhanced ID3 Decision Tree Classifier | Opinion Mining (OM) is a field of Natural Language Processing (NLP) that aims to capture human sentiment in the given text. With the ever-spreading of online purchasing websites, micro-blogging sites, and social media platforms, OM in online social media platforms has picked the interest of thousands of scientific rese... | [
"Opinion Mining",
"Text Classification",
"Sentiment Analysis",
"Information Retrieval",
"Information Extraction & Text Mining"
] | [
49,
36,
78,
24,
3
] |
SCOPUS_ID:85052876674 | A MapReduce implementation of posterior probability clustering and relevance models for recommendation | Relevance-Based Language Models are a formal probabilistic approach for explicitly introducing the concept of relevance in the Statistical Language Modelling framework. Recently, they have been determined as a very effective way of computing recommendations. When combining this new recommendation approach with Posterio... | [
"Language Models",
"Semantic Text Processing",
"Information Extraction & Text Mining",
"Text Clustering"
] | [
52,
72,
3,
29
] |
https://aclanthology.org//D19-5621/ | A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation | Neural models that eliminate the softmax bottleneck by generating word embeddings (rather than multinomial distributions over a vocabulary) attain faster training with fewer learnable parameters. These models are currently trained by maximizing densities of pretrained target embeddings under von Mises-Fisher distributi... | [
"Machine Translation",
"Semantic Text Processing",
"Representation Learning",
"Text Generation",
"Multilinguality"
] | [
51,
72,
12,
47,
0
] |
http://arxiv.org/abs/2212.12800v1 | A Marker-based Neural Network System for Extracting Social Determinants of Health | Objective. The impact of social determinants of health (SDoH) on patients' healthcare quality and the disparity is well-known. Many SDoH items are not coded in structured forms in electronic health records. These items are often captured in free-text clinical notes, but there are limited methods for automatically extra... | [
"Named Entity Recognition",
"Information Retrieval",
"Text Classification",
"Information Extraction & Text Mining"
] | [
34,
24,
36,
3
] |
SCOPUS_ID:85082433072 | A Markov Mixed-Effect Multinomial Logistic Regression Model for Nominal Repeated Measures with an Application to Syntactic Self-Priming Effects | Syntactic priming effects have been investigated for several decades in psycholinguistics and the cognitive sciences to understand the cognitive mechanisms that support language production and comprehension. The question of whether speakers prime themselves is central to adjudicating between two theories of syntactic p... | [
"Psycholinguistics",
"Linguistics & Cognitive NLP",
"Syntactic Text Processing",
"Linguistic Theories"
] | [
77,
48,
15,
57
] |
SCOPUS_ID:85042135102 | A Markov Network Based Passage Retrieval Method for Multimodal Question Answering in the Cultural Heritage Domain | In this paper, we propose a Markov network based graphical framework to perform passage retrieval for multimodal question answering (MQA) with weak supervision in the cultural heritage domain. This framework encodes the dependencies between a question’s feature information and the passage containing its answer, with th... | [
"Question Answering",
"Natural Language Interfaces",
"Passage Retrieval",
"Information Retrieval",
"Multimodality"
] | [
27,
11,
66,
24,
74
] |
SCOPUS_ID:84894561476 | A Markov chain based line segmentation framework for handwritten character recognition | In this paper, we present a novel text line segmentation framework following the divide-and-conquer paradigm: we iteratively identify and re-process regions of ambiguous line segmentation from an input document image until there is no ambiguity. To detect ambiguous line segmentation, we introduce the use of two complim... | [
"Text Segmentation",
"Syntactic Text Processing"
] | [
21,
15
] |
SCOPUS_ID:85057319564 | A Markov logic networks based method to predict judicial decisions of divorce cases | Prediction of the judicial decision of a case is a research issue of artificial intelligence in legal domain. Existing studies mainly focus on criminal cases and aim at charge prediction, moreover the results of these models are usually hard to interpret. In this paper we propose a Markov logic networks based method fo... | [
"Explainability & Interpretability in NLP",
"Responsible & Trustworthy NLP",
"Information Extraction & Text Mining"
] | [
81,
4,
3
] |
SCOPUS_ID:85132943657 | A Mask-Guided Transformer Network with Topic Token for Remote Sensing Image Captioning | Remote sensing image captioning aims to describe the content of images using natural language. In contrast with natural images, the scale, distribution, and number of objects generally vary in remote sensing images, making it hard to capture global semantic information and the relationships between objects at different... | [
"Visual Data in NLP",
"Language Models",
"Semantic Text Processing",
"Captioning",
"Text Generation",
"Multimodality"
] | [
20,
52,
72,
39,
47,
74
] |
http://arxiv.org/abs/2204.09851v2 | A Masked Image Reconstruction Network for Document-level Relation Extraction | Document-level relation extraction aims to extract relations among entities within a document. Compared with its sentence-level counterpart, Document-level relation extraction requires inference over multiple sentences to extract complex relational triples. Previous research normally complete reasoning through informat... | [
"Visual Data in NLP",
"Language Models",
"Information Extraction & Text Mining",
"Semantic Text Processing",
"Relation Extraction",
"Multimodality"
] | [
20,
52,
3,
72,
75,
74
] |
http://arxiv.org/abs/2104.07829v2 | A Masked Segmental Language Model for Unsupervised Natural Language Segmentation | Segmentation remains an important preprocessing step both in languages where "words" or other important syntactic/semantic units (like morphemes) are not clearly delineated by white space, as well as when dealing with continuous speech data, where there is often no meaningful pause between words. Near-perfect supervise... | [
"Language Models",
"Low-Resource NLP",
"Semantic Text Processing",
"Responsible & Trustworthy NLP"
] | [
52,
80,
72,
4
] |
http://arxiv.org/abs/2109.06324v1 | A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space | In cross-lingual language models, representations for many different languages live in the same space. Here, we investigate the linguistic and non-linguistic factors affecting sentence-level alignment in cross-lingual pretrained language models for 101 languages and 5,050 language pairs. Using BERT-based LaBSE and BiLS... | [
"Language Models",
"Semantic Text Processing",
"Morphology",
"Syntactic Text Processing",
"Representation Learning",
"Cross-Lingual Transfer",
"Multilinguality"
] | [
52,
72,
73,
15,
12,
19,
0
] |
https://aclanthology.org//W18-6534/ | A Master-Apprentice Approach to Automatic Creation of Culturally Satirical Movie Titles | Satire has played a role in indirectly expressing critique towards an authority or a person from time immemorial. We present an autonomously creative master-apprentice approach consisting of a genetic algorithm and an NMT model to produce humorous and culturally apt satire out of movie titles automatically. Furthermore... | [
"Text Generation"
] | [
47
] |
SCOPUS_ID:85142014138 | A Matching Method of Oral Text to Instruction Based on Word Vector | Short oral texts have the characteristics of sparse features and vague expressions, which lead to poor performance when applying matching methods to them. Aiming at these problems, this paper proposes a matching method based on word vector text representation, which comprehensively considers part-of-speech, semantics a... | [
"Multimodality",
"Semantic Text Processing",
"Representation Learning"
] | [
74,
72,
12
] |
http://arxiv.org/abs/cmp-lg/9508005v1 | A Matching Technique in Example-Based Machine Translation | This paper addresses an important problem in Example-Based Machine Translation (EBMT), namely how to measure similarity between a sentence fragment and a set of stored examples. A new method is proposed that measures similarity according to both surface structure and content. A second contribution is the use of cluster... | [
"Machine Translation",
"Text Generation",
"Multilinguality"
] | [
51,
47,
0
] |
SCOPUS_ID:85090094971 | A Matching-Integration-Verification Model for Multiple-Choice Reading Comprehension | Multiple-choice reading comprehension is a challenging task requiring a machine to select the correct answer from a candidate answers set. In this paper, we propose a model following a matching-integration-verification-prediction framework, which explicitly employs a verification module inspired by the human being and ... | [
"Reasoning",
"Machine Reading Comprehension"
] | [
8,
37
] |
http://arxiv.org/abs/2010.03648v2 | A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks | Autoregressive language models, pretrained using large text corpora to do well on next word prediction, have been successful at solving many downstream tasks, even with zero-shot usage. However, there is little theoretical understanding of this success. This paper initiates a mathematical study of this phenomenon for t... | [
"Language Models",
"Semantic Text Processing",
"Information Retrieval",
"Reasoning",
"Numerical Reasoning",
"Text Classification",
"Information Extraction & Text Mining"
] | [
52,
72,
24,
8,
5,
36,
3
] |
SCOPUS_ID:85124051475 | A Mathematical Model for Universal Semantics | We characterize the meaning of words with language-independent numerical fingerprints, through a mathematical analysis of recurring patterns in texts. Approximating texts by Markov processes on a long-range time scale, we are able to extract topics, discover synonyms, and sketch semantic fields from a particular docume... | [
"Natural Language Interfaces",
"Reasoning",
"Numerical Reasoning",
"Question Answering"
] | [
11,
8,
5,
27
] |
http://arxiv.org/abs/cs/0504022v1 | A Matter of Opinion: Sentiment Analysis and Business Intelligence (position paper) | A general-audience introduction to the area of "sentiment analysis", the computational treatment of subjective, opinion-oriented language (an example application is determining whether a review is "thumbs up" or "thumbs down"). Some challenges, applications to business-intelligence tasks, and potential future direction... | [
"Opinion Mining",
"Sentiment Analysis"
] | [
49,
78
] |
SCOPUS_ID:85043242485 | A Matter of Perspective: A Discursive Analysis of the Perceptions of Three Stakeholders of the Mutianyu Great Wall | This study aims to investigate the different and competing perspectives of stakeholders of cultural heritage sites by examining the Mutianyu Great Wall in China. Literature review: Most studies focus on investigating the tourism destination image from the perspective of only one stakeholder, and only a small amount of ... | [
"Discourse & Pragmatics",
"Visual Data in NLP",
"Semantic Text Processing",
"Multimodality"
] | [
71,
20,
72,
74
] |
SCOPUS_ID:33746802824 | A Maximal Figure-of-Merit (MFoM)-learning approach to robust classifier design for text categorization | We propose a maximal figure-of-merit (MFoM)-learning approach for robust classifier design, which directly optimizes performance metrics of interest for different target classifiers. The proposed approach, embedding the decision functions of classifiers and performance metrics into an overall training objective, learns... | [
"Information Extraction & Text Mining",
"Text Classification",
"Robustness in NLP",
"Information Retrieval",
"Responsible & Trustworthy NLP"
] | [
3,
36,
58,
24,
4
] |
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