LEADER 03522oam 22005295 450 001 996547972303316 005 20231106224206.0 010 $a981-9938-85-6 024 7 $a10.1007/978-981-99-3885-8 035 $a(MiAaPQ)EBC30722823 035 $a(Au-PeEL)EBL30722823 035 $a(DE-He213)978-981-99-3885-8 035 $a(OCoLC) 1396062057 035 $a(PPN)272263273 035 $a(EXLCZ)9928100239100041 100 $a20230829d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntent recognition for human-machine interactions /$fHua Xu, Hanlei Zhang, Ting-En Lin 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (162 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5776 311 08$aPrint version: Xu, Hua Intent Recognition for Human-Machine Interactions Singapore : Springer,c2023 9789819938841 327 $aPart 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. 330 $aNatural interaction is one of the hottest research issues in human-computer interaction. At present, there is an urgent need for intelligent devices (service robots, virtual humans, etc.) to be able to understand intentions in an interactive dialogue. Focusing on human-computer understanding based on deep learning methods, the book systematically introduces readers to intention recognition, unknown intention detection, and new intention discovery in human-computer dialogue. This book is the first to present interactive dialogue intention analysis in the context of natural interaction. In addition to helping readers master the key technologies and concepts of human-machine dialogue intention analysis and catch up on the latest advances, it includes valuable references for further research. 410 0$aSpringerBriefs in Computer Science,$x2191-5776 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aIntention (Logic) 615 0$aUser interfaces (Computer systems). 615 0$aHuman-computer interaction. 615 0$aIntention (Logic) 676 $a004.019 700 $aXu$b Hua$c(Writer on computer science)$01432277 701 $aZhang$b Hanlei$01423707 701 $aLin$b Ting-En$01423708 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996547972303316 996 $aIntent recognition for human-machine interactions$93576661 997 $aUNISA