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-              <a href="https://github.com/thuiar/Books/tree/main/%E9%9D%A2%E5%90%91%E5%85%B1%E8%9E%8D%E6%9C%BA%E5%99%A8%E4%BA%BA%E7%9A%84%E8%87%AA%E7%84%B6%E4%BA%A4%E4%BA%92%E2%80%94%E2%80%94%E5%A4%9A%E6%A8%A1%E6%80%81%E4%BA%A4%E4%BA%92%E4%BF%A1%E6%81%AF%E7%9A%84%E6%83%85%E6%84%9F%E5%88%86%E6%9E%90" >Multi-modal Sentiment Analysis</a>
+              <a href="https://github.com/thuiar/Books/tree/main/Multi-Modal-Sentiment-Analysis" >Multi-modal Sentiment Analysis</a>
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-                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. The full codes are available for use at <a href="https://github.com/thuiar/Books/tree/main/%E9%9D%A2%E5%90%91%E5%85%B1%E8%9E%8D%E6%9C%BA%E5%99%A8%E4%BA%BA%E7%9A%84%E8%87%AA%E7%84%B6%E4%BA%A4%E4%BA%92%E2%80%94%E2%80%94%E5%A4%9A%E6%A8%A1%E6%80%81%E4%BA%A4%E4%BA%92%E4%BF%A1%E6%81%AF%E7%9A%84%E6%83%85%E6%84%9F%E5%88%86%E6%9E%90" >this link</a>.     
+                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. The full codes are available for use at <a href="https://github.com/thuiar/Books/tree/main/Multi-Modal-Sentiment-Analysis" >this link</a>.     
 
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