articleACM SIGKDD Explorations NewsletterNov 21, 2017Closed access

A Survey on Dialogue Systems

Jingdong (China) · Michigan State University

Indexed incrossref

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…

Citation impact

530
total citations
FWCI
24.35
Percentile
100%
References
137
Citations per year

Authors

4

Topics & keywords

Keywords
  • Computer science
  • Leverage (statistics)
  • Deep learning
  • Data science
  • Artificial intelligence
  • Task (project management)
  • Recommender system
  • Human–computer interaction
UN Sustainable Development Goals
  • Quality Education
No related works found for this paper.