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008 | 231126s2023 si | s |||| 0|eng d | ||
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_aXu, Hua. _eauthor. _0(orcid)0000-0002-7401-307X _1https://orcid.org/0000-0002-7401-307X _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aMulti-Modal Sentiment Analysis _h[electronic resource] / _cby Hua Xu. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2023. |
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300 |
_aXXI, 261 p. 1 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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500 | _aAcceso multiusuario | ||
505 | 0 | _aChapter 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. | |
520 | _aThe 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. | ||
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_fUABC ; _cPerpetuidad |
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650 | 0 | _aComputational intelligence. | |
650 | 0 | _aUser interfaces (Computer systems). | |
650 | 0 | _aHuman-computer interaction. | |
650 | 0 | _aData mining. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aRobotics. | |
650 | 1 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aUser Interfaces and Human Computer Interaction. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aRobotics. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789819957750 |
776 | 0 | 8 |
_iPrinted edition: _z9789819957774 |
776 | 0 | 8 |
_iPrinted edition: _z9789819957781 |
856 | 4 | 0 |
_zLibro electrónico _uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-99-5776-7 |
912 | _aZDB-2-INR | ||
912 | _aZDB-2-SXIT | ||
942 | _cLIBRO_ELEC | ||
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