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Multi Modal Sentiment Analysis
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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 Recent Innovations in Computing by : Pradeep Kumar Singh
Download or read book Recent Innovations in Computing written by Pradeep Kumar Singh and published by Springer Nature. This book was released on 2021-01-12 with total page 846 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features selected papers presented at the 3rd International Conference on Recent Innovations in Computing (ICRIC 2020), held on 20–21 March 2020 at the Central University of Jammu, India, and organized by the university’s Department of Computer Science & Information Technology. It includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.
Book Synopsis Handbook Of Pattern Recognition And Computer Vision (2nd Edition) by : Chi Hau Chen
Download or read book Handbook Of Pattern Recognition And Computer Vision (2nd Edition) written by Chi Hau Chen and published by World Scientific. This book was released on 1999-03-12 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
Book Synopsis Multimodal Analytics for Next-Generation Big Data Technologies and Applications by : Kah Phooi Seng
Download or read book Multimodal Analytics for Next-Generation Big Data Technologies and Applications written by Kah Phooi Seng and published by Springer. This book was released on 2019-07-18 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.
Book Synopsis Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks by : Arindam Chaudhuri
Download or read book Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks written by Arindam Chaudhuri and published by Springer. This book was released on 2019-04-06 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.
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 Multimodal Behavior Analysis in the Wild by : Xavier Alameda-Pineda
Download or read book Multimodal Behavior Analysis in the Wild written by Xavier Alameda-Pineda and published by Academic Press. This book was released on 2018-11-13 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. - Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios - Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources - Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data
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 High-Performance Modelling and Simulation for Big Data Applications by : Joanna Kołodziej
Download or read book High-Performance Modelling and Simulation for Big Data Applications written by Joanna Kołodziej and published by Springer. This book was released on 2019-03-25 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
Book Synopsis Music Emotion Recognition by : Yi-Hsuan Yang
Download or read book Music Emotion Recognition written by Yi-Hsuan Yang and published by CRC Press. This book was released on 2011-02-22 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with
Book Synopsis Proceedings of the 18th ACM International Conference on Multimodal Interaction by : Yukiko I. Nakano
Download or read book Proceedings of the 18th ACM International Conference on Multimodal Interaction written by Yukiko I. Nakano and published by . This book was released on 2016-11-12 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ICMI '16: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION Nov 12, 2016-Nov 16, 2016 Tokyo, Japan. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Book Synopsis Prominent Feature Extraction for Sentiment Analysis by : Basant Agarwal
Download or read book Prominent Feature Extraction for Sentiment Analysis written by Basant Agarwal and published by Springer. This book was released on 2015-12-14 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.
Book Synopsis Deep Learning-Based Approaches for Sentiment Analysis by : Basant Agarwal
Download or read book Deep Learning-Based Approaches for Sentiment Analysis written by Basant Agarwal and published by Springer Nature. This book was released on 2020-01-24 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.
Book Synopsis Affective Computing and Sentiment Analysis by : Khurshid Ahmad
Download or read book Affective Computing and Sentiment Analysis written by Khurshid Ahmad and published by Springer Science & Business Media. This book was released on 2011-08-24 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect – including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated. This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology.
Book Synopsis Appraisal Processes in Emotion by : Klaus R. Scherer
Download or read book Appraisal Processes in Emotion written by Klaus R. Scherer and published by Oxford University Press. This book was released on 2001-05-03 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scientific study of emotion has long been dominated by theories emphasizing the subjective experience of emotions and their accompanying expressive and physiological responses. The processes by which different emotions are elicited has received less attention, the implicit assumption being that certain emotions arise automatically in response to certain types of events or situations. Such an assumption is incompatible with data showing that similar situations can provoke a range of emotions in different individuals, or even the same individual at different times. Appraisal theory, first suggested by Magda Arnold and Richard Lazarus, was formulated to address this shortcoming in our understanding of emotion. The central tenet of appraisal theory is that emotions are elicited according to an individual's subjective interpretation or evaluation of important events or situations. Appraisal research focuses on identifying the evaluative dimensions or criteria that predict which emotion will be elicited in an individual, as well as linking the appraisal process with the production of emotional responses. This book represents the first full-scale summary of the current state of appraisal research. Separate sections cover the history of apraisal theory and its fundamental ideas, the views of some of the major theorists currently active in the field, theoretical and methodological problems with the appraisal approach including suggestions for their resolution, social, cultural and individual differences and the application of appraisal theory to understanding and treating emotional pathology, and the methodology used in appraisal research including measuring and analyzing self-report, physiological, facial, and vocal indicators of appraisal, and simulating appraisal processes via computational models. Intended for advanced students and researchers in emotion psychology, it provides an authoritative assessment and critique of the current state of the art in appraisal research.
Book Synopsis Algorithms and Architectures for Parallel Processing by : Meikang Qiu
Download or read book Algorithms and Architectures for Parallel Processing written by Meikang Qiu and published by Springer Nature. This book was released on 2020-09-29 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNCS 12452, 12453, and 12454 constitutes the proceedings of the 20th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2020, in New York City, NY, USA, in October 2020. The total of 142 full papers and 5 short papers included in this proceedings volumes was carefully reviewed and selected from 495 submissions. ICA3PP is covering the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems. As applications of computing systems have permeated in every aspects of daily life, the power of computing system has become increasingly critical. This conference provides a forum for academics and practitioners from countries around the world to exchange ideas for improving the efficiency, performance, reliability, security and interoperability of computing systems and applications. ICA3PP 2020 focus on two broad areas of parallel and distributed computing, i.e. architectures, algorithms and networks, and systems and applications.
Book Synopsis Computing Attitude and Affect in Text: Theory and Applications by : James G. Shanahan
Download or read book Computing Attitude and Affect in Text: Theory and Applications written by James G. Shanahan and published by Springer Science & Business Media. This book was released on 2006-01-17 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the “factual” aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author’s reports from reports of other people’s opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers’ aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an “NLP”-complete problem.
