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Lifelong and Continual Learning Dialogue Systems de Sahisnu Mazumder

Lifelong and Continual Learning Dialogue Systems: Synthesis Lectures on Human Language Technologies

Autor Sahisnu Mazumder, Bing Liu
en Limba Engleză Hardback – 10 ian 2024
This book introduces the new paradigm of lifelong and continual learning dialogue systems to endow dialogue systems with the ability to learn continually by themselves through their own self-initiated interactions with their users and the working environments. The authors present the latest developments and techniques for building such continual learning dialogue systems.  The book explains how these developments allow systems to continuously learn new language expressions,   lexical and factual knowledge, and conversational skills through interactions and dialogues.  Additionally, the book covers techniques to acquire new training examples for learning new tasks during the conversation. The book also reviews existing work on lifelong learning and discusses areas for future research. 
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Specificații

ISBN-13: 9783031481888
ISBN-10: 3031481887
Pagini: 171
Ilustrații: XVI, 171 p. 64 illus., 55 illus. in color.
Dimensiuni: 168 x 240 mm
Greutate: 0.52 kg
Ediția:1st ed. 2024
Editura: Springer International Publishing
Colecția Springer
Seria Synthesis Lectures on Human Language Technologies

Locul publicării:Cham, Switzerland

Cuprins

1 Introduction.- 2 Open-world Continual Learning: A Framework.- 3 Continuous Factual Knowledge Learning in Dialogues.- 4 Continuous and Interactive Language Learning and Grounding.- 5 Continual Learning in Chit-chat Systems.- 6 Continual Learning for Task-oriented Dialogue Systems.- 7 Continual Learning of Conversational Skills.- 8 Conclusion and Future Directions.

Notă biografică

Sahisnu Mazumder is an AI Research Scientist at Intel Labs, USA, where he works on human-AI collaboration and dialogue and interactive systems research. He obtained his Ph.D. in Computer Science at the University of Illinois at Chicago, USA, and his Masters in Computer Science from the Indian Institute of Technology (IIT), Roorkee, India. His research interests include lifelong and continual learning, dialogue and interactive systems, open-world AI and learning, knowledge base reasoning, and sentiment analysis.  He has published several research papers in these areas in leading AI, NLP and Dialogue conferences and given two tutorial talks on this book topic.  During his Ph.D,, he also worked as a Research Intern at Microsoft Research Redmond and Huawei Research USA on virtual AI Assistants. 
Bing Liu is a Distinguished Professor of Computer Science at the University of Illinois at Chicago, USA. He received his Ph.D. in Artificial Intelligence from the University of Edinburgh, UK. His research interests include lifelong and continual learning, lifelong learning dialogue systems, open-world learning, sentiment analysis and opinion mining, machine learning, and natural language processing. He has published extensively in top conferences and journals in these areas and has authored four books. Three of his papers have received Test-of-Time awards and another received Test-of-Time honorable mention.  He is the winner of 2018 ACM SIGKDD Innovation Award and is a Fellow of AAAI, ACM, and IEEE.

Textul de pe ultima copertă

This book introduces the new paradigm of lifelong and continual learning dialogue systems to endow dialogue systems with the ability to learn continually by themselves through their own self-initiated interactions with their users and the working environments. The authors present the latest developments and techniques for building such continual learning dialogue systems.  The book explains how these developments allow systems to continuously learn new language expressions,   lexical and factual knowledge, and conversational skills through interactions and dialogues.  Additionally, the book covers techniques to acquire new training examples for learning new tasks during the conversation. The book also reviews existing work on lifelong learning and discusses areas for future research.
  • Provides background on the categories of dialogue systems, including their problems and weaknesses
  • Provides a framework for open-world continual learning and explains how it can be used to improve dialogue systems
  • Focuses on how lifelong learning dialogue systems can be built and deployed for practical applications


Caracteristici

Provides background on the categories of dialogue systems, including their problems and weaknesses Provides a framework for open-world continual learning and explains how it can be used to improve dialogue systems Focuses on how lifelong learning dialogue systems can be built and deployed for practical applications