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Focus Based Semantic Analysis
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Book Synopsis Handbook of Natural Language Processing by : Nitin Indurkhya
Download or read book Handbook of Natural Language Processing written by Nitin Indurkhya and published by CRC Press. This book was released on 2010-02-22 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
Book Synopsis Sentiment Analysis in Social Networks by : Federico Alberto Pozzi
Download or read book Sentiment Analysis in Social Networks written by Federico Alberto Pozzi and published by Morgan Kaufmann. This book was released on 2016-10-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics
Download or read book Sentiment Analysis written by Bing Liu and published by Cambridge University Press. This book was released on 2020-10-15 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.
Download or read book Sentiment Analysis written by Bing Liu and published by Cambridge University Press. This book was released on 2020-10-15 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.
Book Synopsis Opinion Mining and Sentiment Analysis by : Bo Pang
Download or read book Opinion Mining and Sentiment Analysis written by Bo Pang and published by Now Publishers Inc. This book was released on 2008 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
Book Synopsis Stochastically-Based Semantic Analysis by : Wolfgang Minker
Download or read book Stochastically-Based Semantic Analysis written by Wolfgang Minker and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastically-Based Semantic Analysis investigates the problem of automatic natural language understanding in a spoken language dialog system. The focus is on the design of a stochastic parser and its evaluation with respect to a conventional rule-based method. Stochastically-Based Semantic Analysis will be of most interest to researchers in artificial intelligence, especially those in natural language processing, computational linguistics, and speech recognition. It will also appeal to practicing engineers who work in the area of interactive speech systems.
Book Synopsis Opinions, Sentiment, and Emotion in Text by : Bing Liu
Download or read book Opinions, Sentiment, and Emotion in Text written by Bing Liu and published by Cambridge University Press. This book was released on 2015-06-04 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a comprehensive introduction to all the core areas and many emerging themes of sentiment analysis.
Book Synopsis New Frontiers in Artificial Intelligence by : Maki Sakamoto
Download or read book New Frontiers in Artificial Intelligence written by Maki Sakamoto and published by Springer Nature. This book was released on 2020-09-13 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes extended, revised and selected papers from the 11th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2019. It was held in November 2019 in Yokohama, Japan. The 26 papers were carefully selected from 46 submissions and deal with topics of AI research and are organized into 4 sections, according to the 4 workshops: JURISIN 2019, AI-Biz 2019, LENLS 16, and Kansei-AI 2019.
Book Synopsis Sentiment Analysis and Opinion Mining by : Bing Liu
Download or read book Sentiment Analysis and Opinion Mining written by Bing Liu and published by Springer Nature. This book was released on 2022-05-31 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
Book Synopsis Multi-Modal Sentiment Analysis by : Hua Xu
Download or read book Multi-Modal Sentiment Analysis written by Hua Xu and published by Springer Nature. This book was released on 2023-11-26 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields.
Book Synopsis Semantic Similarity from Natural Language and Ontology Analysis by : Sébastien Harispe
Download or read book Semantic Similarity from Natural Language and Ontology Analysis written by Sébastien Harispe and published by Morgan & Claypool Publishers. This book was released on 2015-05-01 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better understanding of semantic similarity estimation and more generally semantic measures. To this end, we propose an in-depth characterization of existing proposals by discussing their features, the assumptions on which they are based and empirical results regarding their performance in particular applications. By answering these questions and by providing a detailed discussion on the foundations of semantic measures, our aim is to give the reader key knowledge required to: (i) select the more relevant methods according to a particular usage context, (ii) understand the challenges offered to this field of study, (iii) distinguish room of improvements for state-of-the-art approaches and (iv) stimulate creativity toward the development of new approaches. In this aim, several definitions, theoretical and practical details, as well as concrete applications are presented
Book Synopsis Advanced Concepts, Methods, and Applications in Semantic Computing by : Daramola, Olawande
Download or read book Advanced Concepts, Methods, and Applications in Semantic Computing written by Daramola, Olawande and published by IGI Global. This book was released on 2020-12-18 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semantic computing is critical for the development of semantic systems and applications that must utilize semantic analysis, semantic description, semantic interfaces, and semantic integration of data and services to deliver their objectives. Semantic computing has enormous capabilities to enhance the efficiency and throughput of systems that are based on key emerging concepts and technologies such as semantic web, internet of things, blockchain technology, and knowledge graphs. Thus, research that expounds advanced concepts, methods, technologies, and applications of semantic computing for solving challenges in real-world domains is vital. Advanced Concepts, Methods, and Applications in Semantic Computing is a scholarly reference book that provides a sound theoretical foundation for the application of semantic methods, concepts, and technologies for practical problem solving. It is designed as a comprehensive and reliable resource on how semantic-oriented approaches can be used to aid new emergent technologies and tackle real-world problems. Covering topics that include deep learning, machine learning, blockchain technology, and semantic web services, this book is ideal for professionals, academicians, researchers, and students working in the field of semantic computing in various disciplines, including but not limited to software engineering, systems engineering, knowledge engineering, electronic commerce, computer science, and information technology.
Download or read book Sentic Computing written by Erik Cambria and published by Springer Science & Business Media. This book was released on 2012-07-28 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality reduction techniques is exploited on two common sense knowledge bases to develop a novel intelligent engine for open-domain opinion mining and sentiment analysis. The proposed approach, termed sentic computing, performs a clause-level semantic analysis of text, which allows the inference of both the conceptual and emotional information associated with natural language opinions and, hence, a more efficient passage from (unstructured) textual information to (structured) machine-processable data.
Book Synopsis Intelligent Information and Database Systems by : Ngoc-Thanh Nguyen
Download or read book Intelligent Information and Database Systems written by Ngoc-Thanh Nguyen and published by Springer. This book was released on 2016-03-08 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume proceedings of the ACIIDS 2016 conference, LNAI 9621 + 9622, constitutes the refereed proceedings of the 8th Asian Conference on Intelligent Information and Database Systems, held in Da Nang, Vietnam, in March 2016. The total of 153 full papers accepted for publication in these proceedings was carefully reviewed and selected from 392 submissions. They were organized in topical sections named: knowledge engineering and semantic Web; social networks and recommender systems; text processing and information retrieval; database systems and software engineering; intelligent information systems; decision support and control systems; machine learning and data mining; computer vision techniques; intelligent big data exploitation; cloud and network computing; multiple model approach to machine learning; advanced data mining techniques and applications; computational intelligence in data mining for complex problems; collective intelligence for service innovation, technology opportunity, e-learning, and fuzzy intelligent systems; analysis for image, video and motion data in life sciences; real world applications in engineering and technology; ontology-based software development; intelligent and context systems; modeling and optimization techniques in information systems, database systems and industrial systems; smart pattern processing for sports; and intelligent services for smart cities.
Book Synopsis Proceedings of the 2012 International Conference on Information Technology and Software Engineering by : Wei Lu
Download or read book Proceedings of the 2012 International Conference on Information Technology and Software Engineering written by Wei Lu and published by Springer Science & Business Media. This book was released on 2012-11-05 with total page 976 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the 2012 International Conference on Information Technology and Software Engineering presents selected articles from this major event, which was held in Beijing, December 8-10, 2012. This book presents the latest research trends, methods and experimental results in the fields of information technology and software engineering, covering various state-of-the-art research theories and approaches. The subjects range from intelligent computing to information processing, software engineering, Web, unified modeling language (UML), multimedia, communication technologies, system identification, graphics and visualizing, etc. The proceedings provide a major interdisciplinary forum for researchers and engineers to present the most innovative studies and advances, which can serve as an excellent reference work for researchers and graduate students working on information technology and software engineering. Prof. Wei Lu, Dr. Guoqiang Cai, Prof. Weibin Liu and Dr. Weiwei Xing all work at Beijing Jiaotong University.
Book Synopsis The Oxford Handbook of Information Structure by : Caroline Féry
Download or read book The Oxford Handbook of Information Structure written by Caroline Féry and published by Oxford University Press. This book was released on 2016-07-21 with total page 993 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides linguists with a clear, critical, and comprehensive overview of theoretical and experimental work on information structure. Leading researchers survey the main theories of information structure in syntax, phonology, and semantics as well as perspectives from psycholinguistics and other relevant fields. Following the editors' introduction the book is divided into four parts. The first, on theories of and theoretical perspectives on information structure, includes chapters on focus, topic, and givenness. Part 2 covers a range of current issues in the field, including quantification, dislocation, and intonation, while Part 3 is concerned with experimental approaches to information structure, including language processing and acquisition. The final part contains a series of linguistic case studies drawn from a wide variety of the world's language families. This volume will be the standard guide to current work in information structure and a major point of departure for future research.
Book Synopsis Machine Learning for Social and Behavioral Research by : Ross Jacobucci
Download or read book Machine Learning for Social and Behavioral Research written by Ross Jacobucci and published by Guilford Publications. This book was released on 2023-05-30 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big Five Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples.