Research Area:  Machine Learning

Abstract:

With the rapid progress of deep neural models and the explosion of available data resources, dialogue systems that supports extensive topics and chit-chat conversations are emerging as a research hot-spot for many communities, e.g., information retrieval (IR), natural language processing (NLP), and machine learning (ML). Building a chit-chat system with retrieval techniques is an essential task and has achieved great success in the past few years. The advance of chit-chat systems, in turn, can support extensive IR tasks, e.g., conversational search and conversational recommendation. To facilitate the development of both retrieval-based chit-chat systems and IR tasks supported by these systems, we survey chit-chat systems from two perspectives: (1) techniques to build chit-chat systems, i.e., deep retrieval-based models, generative methods, and their ensembles, and (2) chit-chat components in completing IR tasks. In each aspect, we present cutting-edge neural methods and summarize the core challenges encountered and possible research directions.

Keywords:  
Deep Learning
Dialogue Systems
Chit-Chat And Beyond
information retrieval (IR)
natural language processing (NLP)
machine learning (ML)

Author(s) Name:  Rui Yan, Juntao Li,Zhou Yu,

Publisher name:  now publishers

DOI:  10.1561/1500000083

Volume Information:  Volume 15 , Issue 5

Paper Link:   https://www.nowpublishers.com/article/Details/INR-083