research-article

A Survey on Dialogue Systems: Recent Advances and New Frontiers

Authors:

Jiliang TangAuthors Info & Claims

ACM SIGKDD Explorations Newsletter, Volume 19, Issue 2

Pages 25 - 35

https://doi.org/10.1145/3166054.3166058

Published: 21 November 2017 Publication History

Abstract

Dialogue systems have attracted more and more attention. Recent advances on dialogue systems are overwhelmingly contributed by deep learning techniques, which have been employed to enhance a wide range of big data applications such as computer vision, natural language processing, and recommender systems. For dialogue systems, deep learning can leverage a massive amount of data to learn meaningful feature representations and response generation strategies, while requiring a minimum amount of hand-crafting. In this article, we give an overview to these recent advances on dialogue systems from various perspectives and discuss some possible research directions. In particular, we generally divide existing dialogue systems into task-oriented and nontask- oriented models, then detail how deep learning techniques help them with representative algorithms and finally discuss some appealing research directions that can bring the dialogue system research into a new frontier

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Index Terms

A Survey on Dialogue Systems: Recent Advances and New Frontiers
1. Computing methodologies
  1. Machine learning
2. Hardware
  1. Power and energy
    1. Power estimation and optimization
      1. Platform power issues

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM SIGKDD Explorations Newsletter

ACM SIGKDD Explorations Newsletter Volume 19, Issue 2

December 2017

46 pages

ISSN:1931-0145

EISSN:1931-0153

DOI:10.1145/3166054

Editors:
Charu Aggarwal
IBM T.J. Watson
,
Haixun Wang
Google
,
Ankur Teredesai
University of Washington Tacoma
,
Hanghang Tong
Arizona State University

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Copyright © 2017 Authors.

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Association for Computing Machinery

New York, NY, United States

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Published: 21 November 2017

Published in SIGKDD Volume 19, Issue 2

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Algherairy AAhmed M(2025)Prompting large language models for user simulation in task-oriented dialogue systemsComputer Speech & Language10.1016/j.csl.2024.10169789(101697)Online publication date: Jan-2025
https://doi.org/10.1016/j.csl.2024.101697
Gyevnar BWang CLucas CCohen SAlbrecht SDastani MSichman JAlechina NDignum V(2024)Causal Explanations for Sequential Decision-Making in Multi-Agent SystemsProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662930(771-779)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3662930
Wu ZShe QZhou C(2024)Intelligent Customer Service System Optimization Based on Artificial IntelligenceJournal of Organizational and End User Computing10.4018/JOEUC.33692336:1(1-27)Online publication date: 21-Feb-2024
https://dl.acm.org/doi/10.4018/JOEUC.336923
Hashimoto KHohjo H(2024)The impacts of vagueness in communication on language evolutionJournal of Dynamics and Games10.3934/jdg.2024012(0-0)Online publication date: 2024
https://doi.org/10.3934/jdg.2024012
Izadi SForouzanfar M(2024)Error Correction and Adaptation in Conversational AI: A Review of Techniques and Applications in ChatbotsAI10.3390/ai50200415:2(803-841)Online publication date: 4-Jun-2024
https://doi.org/10.3390/ai5020041
Uchida TMinato TIshiguro H(2024)Opinion attribution improves motivation to exchange subjective opinions with humanoid robotsFrontiers in Robotics and AI10.3389/frobt.2024.117587911Online publication date: 19-Feb-2024
https://doi.org/10.3389/frobt.2024.1175879
Adhikary PSrivastava AKumar SSingh SManuja PGopinath JKrishnan VGupta SDeb KChakraborty T(2024)Exploring the Efficacy of Large Language Models in Summarizing Mental Health Counseling Sessions: Benchmark StudyJMIR Mental Health10.2196/5730611(e57306)Online publication date: 23-Jul-2024
https://doi.org/10.2196/57306
Dobbala MLingolu M(2024)Conversational AI and Chatbots: Enhancing User Experience on WebsitesAmerican Journal of Computer Science and Technology10.11648/j.ajcst.20240703.117:3(62-70)Online publication date: 29-Jul-2024
https://doi.org/10.11648/j.ajcst.20240703.11
Pei JYan Gde Rijke MRen P(2024)Mixture-of-languages Routing for Multilingual DialoguesACM Transactions on Information Systems10.1145/3676956Online publication date: 5-Aug-2024
https://doi.org/10.1145/3676956
Zhuang HZhang WChen WYang JSheng Q(2024)Improving Faithfulness and Factuality with Contrastive Learning in Explainable RecommendationACM Transactions on Intelligent Systems and Technology10.1145/3653984Online publication date: 25-May-2024
https://doi.org/10.1145/3653984
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