A Multi-Factor Classification Framework for Completing Users’ Fuzzy Queries (Student Abstract)

Authors

  • Yaning Zhang Capital Normal University
  • Liangqing Wu JD AI Research
  • Yangyang Wang JD AI Research
  • Jia Wang JD AI Research
  • Xiaoguang Yu JD AI Research
  • Shuangyong Song JD AI Research
  • Youzheng Wu JD AI Research
  • Xiaodong He JD AI Research

DOI:

https://doi.org/10.1609/aaai.v36i11.21693

Keywords:

Multi-factor Classification, Intent Identification, Fuzzy Queries, Dialogue System

Abstract

Intent identification is the key technology in dialogue system. However, not all online queries are clear or complete. To identify users' intents from those fuzzy queries accurately, this paper proposes a multi-factor classification framework on the query level. Experimental results on our online serving system JIMI demonstrate the effectiveness of our proposed framework.
AAAI-22 Proceedings Cover

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Published

2022-06-28

How to Cite

Zhang, Y., Wu, L., Wang, Y., Wang, J., Yu, X., Song, S., Wu, Y., & He, X. (2022). A Multi-Factor Classification Framework for Completing Users’ Fuzzy Queries (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13113-13114. https://doi.org/10.1609/aaai.v36i11.21693

Issue

Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Section

AAAI Student Abstract and Poster Program