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.