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Intent recognition for human-machine...
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Xu, Hua.
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Intent recognition for human-machine interactions
Record Type:
Electronic resources : Monograph/item
Title/Author:
Intent recognition for human-machine interactions/ by Hua Xu, Hanlei Zhang, Ting-En Lin.
Author:
Xu, Hua.
other author:
Zhang, Hanlei.
Published:
Singapore :Springer Nature Singapore : : 2023.,
Description:
xviii, 152 p. :ill., digital ;24 cm.
[NT 15003449]:
Part I: Overview -- Chapter 1. Dialogue System -- Chapter 2. Intent Recognition -- Part II: Intent Classification -- Chapter 3. Intent Classification Based on Single Model -- Chapter 4. A Dual RNN Semantic Analysis Framework for Intent Classification and Slot -- Part III: Unknown Intent Detection -- Chapter 5. Unknown Intent Detection Method Based on Model Post-processing -- Chapter 6. Unknown Intent Detection Based on Large-Margin Cosine Loss -- Chapter 7. Unknown Intention Detection Method based on Dynamic Constraint Boundary -- Part IV: Discovery of Unknown Intents -- Chapter 8. Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement -- Chapter 9. Discovering New Intents with Deep Aligned Clustering -- Part V: Dialogue Intent Recognition Platform -- Chapter 10. Experiment Platform for Dialogue Intent Recognition based on Deep Learning -- Part VI: Summary and Future Work -- Chapter 11. Summary -- Appendix.
Contained By:
Springer Nature eBook
Subject:
Human-computer interaction. -
Online resource:
https://doi.org/10.1007/978-981-99-3885-8
ISBN:
9789819938858
Intent recognition for human-machine interactions
Xu, Hua.
Intent recognition for human-machine interactions
[electronic resource] /by Hua Xu, Hanlei Zhang, Ting-En Lin. - Singapore :Springer Nature Singapore :2023. - xviii, 152 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5776. - SpringerBriefs in computer science..
Part I: Overview -- Chapter 1. Dialogue System -- Chapter 2. Intent Recognition -- Part II: Intent Classification -- Chapter 3. Intent Classification Based on Single Model -- Chapter 4. A Dual RNN Semantic Analysis Framework for Intent Classification and Slot -- Part III: Unknown Intent Detection -- Chapter 5. Unknown Intent Detection Method Based on Model Post-processing -- Chapter 6. Unknown Intent Detection Based on Large-Margin Cosine Loss -- Chapter 7. Unknown Intention Detection Method based on Dynamic Constraint Boundary -- Part IV: Discovery of Unknown Intents -- Chapter 8. Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement -- Chapter 9. Discovering New Intents with Deep Aligned Clustering -- Part V: Dialogue Intent Recognition Platform -- Chapter 10. Experiment Platform for Dialogue Intent Recognition based on Deep Learning -- Part VI: Summary and Future Work -- Chapter 11. Summary -- Appendix.
Natural interaction is one of the hottest research issues in human-computer interaction. At present, there is an urgent need for intelligent devices (service robots, virtual humans, etc.) to be able to understand intentions in an interactive dialogue. Focusing on human-computer understanding based on deep learning methods, the book systematically introduces readers to intention recognition, unknown intention detection, and new intention discovery in human-computer dialogue. This book is the first to present interactive dialogue intention analysis in the context of natural interaction. In addition to helping readers master the key technologies and concepts of human-machine dialogue intention analysis and catch up on the latest advances, it includes valuable references for further research.
ISBN: 9789819938858
Standard No.: 10.1007/978-981-99-3885-8doiSubjects--Topical Terms:
560071
Human-computer interaction.
LC Class. No.: QA76.9.U83
Dewey Class. No.: 004.019
Intent recognition for human-machine interactions
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Part I: Overview -- Chapter 1. Dialogue System -- Chapter 2. Intent Recognition -- Part II: Intent Classification -- Chapter 3. Intent Classification Based on Single Model -- Chapter 4. A Dual RNN Semantic Analysis Framework for Intent Classification and Slot -- Part III: Unknown Intent Detection -- Chapter 5. Unknown Intent Detection Method Based on Model Post-processing -- Chapter 6. Unknown Intent Detection Based on Large-Margin Cosine Loss -- Chapter 7. Unknown Intention Detection Method based on Dynamic Constraint Boundary -- Part IV: Discovery of Unknown Intents -- Chapter 8. Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement -- Chapter 9. Discovering New Intents with Deep Aligned Clustering -- Part V: Dialogue Intent Recognition Platform -- Chapter 10. Experiment Platform for Dialogue Intent Recognition based on Deep Learning -- Part VI: Summary and Future Work -- Chapter 11. Summary -- Appendix.
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Natural interaction is one of the hottest research issues in human-computer interaction. At present, there is an urgent need for intelligent devices (service robots, virtual humans, etc.) to be able to understand intentions in an interactive dialogue. Focusing on human-computer understanding based on deep learning methods, the book systematically introduces readers to intention recognition, unknown intention detection, and new intention discovery in human-computer dialogue. This book is the first to present interactive dialogue intention analysis in the context of natural interaction. In addition to helping readers master the key technologies and concepts of human-machine dialogue intention analysis and catch up on the latest advances, it includes valuable references for further research.
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