Download or read book Sentiment and Emotion Analysis for Visual and Multimedia Content written by Quanzeng You and published by . This book was released on 2017 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Social multimedia refers to the multimedia content generated by online social network users. The increasing popularity of online social networks accumulates large amounts of social network activity records, making the analysis of online social activities possible. In particular, we research the problem of whether online user' generated content can be employed to understand people's real world lives. The large scale data have attracted people from both industrial and academic communities to mine interesting patterns from the hidden signals in the online users' activities. Researchers have successfully employed the signals extracted from social network content to finish tasks in a wide range of applications, including real world activity prediction and content recommendation. From this perspective, we can view social multimedia as sensors, which provide online signals reflecting people's real world activities. This thesis focuses on sentiment analysis of online social multimedia content. We first propose two approaches to visual sentiment analysis, which is directed to predict human beings' responses towards visual stimuli. Next, we build currently the largest visual emotion dataset, where each image is labeled by five Amazon Mechanical Turkers. Because the lack of high-quality dataset is one of the main difficulties in building effective machine learning models, we expect the release of this dataset will benefit the research community by empowering the development of efficient algorithms for visual emotion analysis. We then conduct a multimodality sentiment analysis. Two different approaches are proposed. The first approach tries to enforce a consistency between the prediction results from textual and visual signal respectively. The second method attempts to match textual and visual concepts and produces robust representations for the sentiment classification model. Furthermore, we try to automatically generate sentiment-bearing image captions with different sentiment labels. The results suggest that the model can focus on different image regions to produce the matching sentiment related descriptions."--Pages xiv-xv.
Download or read book Visual and Text Sentiment Analysis Through Hierarchical Deep Learning Networks written by Arindam Chaudhuri and published by . This book was released on 2019 with total page 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 Frontiers of Multimedia Research written by Shih-Fu Chang and published by Morgan & Claypool. This book was released on 2018-01-03 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of multimedia is unique in offering a rich and dynamic forum for researchers from “traditional” fields to collaborate and develop new solutions and knowledge that transcend the boundaries of individual disciplines. Despite the prolific research activities and outcomes, however, few efforts have been made to develop books that serve as an introduction to the rich spectrum of topics covered by this broad field. A few books are available that either focus on specific subfields or basic background in multimedia. Tutorial-style materials covering the active topics being pursued by the leading researchers at frontiers of the field are currently lacking. In 2015, ACM SIGMM, the special interest group on multimedia, launched a new initiative to address this void by selecting and inviting 12 rising-star speakers from different subfields of multimedia research to deliver plenary tutorial-style talks at the ACM Multimedia conference for 2015. Each speaker discussed the challenges and state-of-the-art developments of their prospective research areas in a general manner to the broad community. The covered topics were comprehensive, including multimedia content understanding, multimodal human-human and human-computer interaction, multimedia social media, and multimedia system architecture and deployment. Following the very positive responses to these talks, the speakers were invited to expand the content covered in their talks into chapters that can be used as reference material for researchers, students, and practitioners. Each chapter discusses the problems, technical challenges, state-of-the-art approaches and performances, open issues, and promising direction for future work. Collectively, the chapters provide an excellent sampling of major topics addressed by the community as a whole. This book, capturing some of the outcomes of such efforts, is well positioned to fill the aforementioned needs in providing tutorial-style reference materials for frontier topics in multimedia. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too. This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing. We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective. This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.
Download or read book MultiMedia Modeling written by Yong Man Ro and published by Springer Nature. This book was released on 2019-12-27 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 11961 and 11962 constitutes the thoroughly refereed proceedings of the 25th International Conference on MultiMedia Modeling, MMM 2020, held in Daejeon, South Korea, in January 2020. Of the 171 submitted full research papers, 40 papers were selected for oral presentation and 46 for poster presentation; 28 special session papers were selected for oral presentation and 8 for poster presentation; in addition, 9 demonstration papers and 6 papers for the Video Browser Showdown 2020 were accepted. The papers of LNCS 11961 are organized in the following topical sections: audio and signal processing; coding and HVS; color processing and art; detection and classification; face; image processing; learning and knowledge representation; video processing; poster papers; the papers of LNCS 11962 are organized in the following topical sections: poster papers; AI-powered 3D vision; multimedia analytics: perspectives, tools and applications; multimedia datasets for repeatable experimentation; multi-modal affective computing of large-scale multimedia data; multimedia and multimodal analytics in the medical domain and pervasive environments; intelligent multimedia security; demo papers; and VBS papers.
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.
Download or read book Recent Advancements in Multimedia Data Processing and Security Issues Challenges and Techniques written by Abd El-Latif, Ahmed A. and published by IGI Global. This book was released on 2023-09-28 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of social media dominance, a staggering amount of textual data floods our online spaces daily. While this wealth of information presents boundless opportunities for research and understanding human behavior, it also poses substantial challenges. The sheer volume of data overwhelms traditional processing methods, and harnessing its potential requires sophisticated tools. Furthermore, the need for ensuring data security and mitigating risks in the digital realm has never been more pressing. Academic scholars, researchers, and professionals grapple with these issues daily, seeking innovative solutions to unlock the true value of multimedia data while safeguarding privacy and integrity. Recent Advancements in Multimedia Data Processing and Security: Issues, Challenges, and Techniques is a groundbreaking book that serves as a beacon of light amidst the sea of data-related challenges. It offers a comprehensive solution by bridging the gap between academic research and practical applications. By delving into topics such as deep learning, emotion recognition, and high-dimensional text clustering, it equips scholars and professionals with the innovative tools and techniques they need to navigate the complex landscape of multimedia 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.
Download or read book Multimodal Analysis of User Generated Multimedia Content written by Rajiv Shah and published by Springer. This book was released on 2017-08-30 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a summary of the multimodal analysis of user-generated multimedia content (UGC). Several multimedia systems and their proposed frameworks are also discussed. First, improved tag recommendation and ranking systems for social media photos, leveraging both content and contextual information, are presented. Next, we discuss the challenges in determining semantics and sentics information from UGC to obtain multimedia summaries. Subsequently, we present a personalized music video generation system for outdoor user-generated videos. Finally, we discuss approaches for multimodal lecture video segmentation techniques. This book also explores the extension of these multimedia system with the use of heterogeneous continuous streams.
Download or read book Sentiment Analysis and Knowledge Discovery in Contemporary Business written by Rajput, Dharmendra Singh and published by IGI Global. This book was released on 2018-08-31 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit.
Download or read book Multimedia Data Mining and Analytics written by Aaron K. Baughman and published by Springer. This book was released on 2015-03-31 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.
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 98 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 Proceedings of International Conference on Computational Intelligence Data Science and Cloud Computing written by Valentina Emilia Balas and published by Springer Nature. This book was released on 2021 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.
Download or read book Multimodal Sentiment Analysis written by Soujanya Poria and published by . This book was released on 2018 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches.
Download or read book Proceedings of the Future Technologies Conference FTC 2021 Volume 2 written by Kohei Arai and published by Springer Nature. This book was released on 2021-11-03 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a wide range of important topics including but not limited to Technology Trends, Computing, Artificial Intelligence, Machine Vision, Communication, Security, e-Learning, and Ambient Intelligence and their applications to the real world. The sixth Future Technologies Conference 2021 was organized virtually and received a total of 531 submissions from academic pioneering researchers, scientists, industrial engineers, and students from all over the world. After a double-blind peer review process, 191 submissions have been selected to be included in these proceedings. One of the meaningful and valuable dimensions of this conference is the way it brings together a large group of technology geniuses in one venue to not only present breakthrough research in future technologies, but also to promote discussions and debate of relevant issues, challenges, opportunities and research findings. We hope that readers find the book interesting, exciting, and inspiring; it provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.
Download or read book Sentiment Analysis for Social Media written by Carlos A. Iglesias and published by . This book was released on 2020 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.
Download or read book MultiMedia Modeling written by Yong Man Ro and published by Springer Nature. This book was released on 2019-12-27 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 11961 and 11962 constitutes the thoroughly refereed proceedings of the 25th International Conference on MultiMedia Modeling, MMM 2020, held in Daejeon, South Korea, in January 2020. Of the 171 submitted full research papers, 40 papers were selected for oral presentation and 46 for poster presentation; 28 special session papers were selected for oral presentation and 8 for poster presentation; in addition, 9 demonstration papers and 6 papers for the Video Browser Showdown 2020 were accepted. The papers of LNCS 11961 are organized in the following topical sections: audio and signal processing; coding and HVS; color processing and art; detection and classification; face; image processing; learning and knowledge representation; video processing; poster papers; the papers of LNCS 11962 are organized in the following topical sections: poster papers; AI-powered 3D vision; multimedia analytics: perspectives, tools and applications; multimedia datasets for repeatable experimentation; multi-modal affective computing of large-scale multimedia data; multimedia and multimodal analytics in the medical domain and pervasive environments; intelligent multimedia security; demo papers; and VBS papers.
