Buch, Englisch, 261 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 435 g
ISBN: 978-981-99-5778-1
Verlag: Springer Nature Singapore
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
Weitere Infos & Material
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.