Multi-Modal Sentiment Analysis - Xu, Hua

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Résumé :
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.

Biographie:
Hua Xu is a leading expert on Intelligent Natural Interaction and Service Robots. He is currently a tenured associate professor at Tsinghua University, Editor-in-Chief of Intelligent Systems with Applications and Associate Editor of Expert Systems with Application. Prof. Xu has authored the books Data Mining: Methodology and Applications (2014), Data Mining: Methods and Applications-Application Cases (2017), Evolutionary Machine Learning (2021), Data Mining: Methodology and Applications (2nd edition) (2022), Natural Interaction for Tri-Co Robots (1) Human-machine Dialogue Intention Understanding (2022) and Natural Interaction for Tri-Co Robots (2) Sentiment Analysis of Multimodal Interaction Information (2023), and published more than 140 papers in top-tier international journals and conferences. He is core expert of the No. 3 National Science and Technology Major Project of the Ministry of Industry and Information Technology of China, Senior Memberof CCF, member of CAAI and ACM, Vice Chairman of Tsinghua Collaborative Innovation Alliance of Robotics and Industry, and recipient of numerous awards, including the Second Prize of National Award for Progress in Science and Technology, First Prize for Technological Invention of CFLP, and First Prize for Science and Technology Progress of CFLP....

Sommaire:

Chapter 1. Overview.- Chapter 2. Multimodal Sentiment Analysis Data sets and Preprocessing.- Chapter 3. Early Unimodal Sentiment Analysis of Comment Text based on Traditional Machine Learning.- Chapter 4. Unimodal Sentiment Analysis.- Chapter 5. Cross-Modal Sentiment Analysis.- Chapter 6. Multimodal Sentiment Analysis.- Chapter 7. Multimodal Sentiment Analysis Platform and Application.- Appendix.