• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
搜索

Author:

Zhang, Wangyang (Zhang, Wangyang.) | Fan, Qingwu (Fan, Qingwu.) | Liu, Xudong (Liu, Xudong.) | Sun, Jialin (Sun, Jialin.)

Indexed by:

EI Scopus

Abstract:

In order to solve the problem that it is difficult to efficiently identify homologous complaints and reports in dealing with complaints and reports, this paper proposes to detect homologous complaint reports in the decomposed attention network. Firstly, TextCNN is used to extract local features of complaint reports text, and then the matching task between features is carried out. Due to the high noise of the complaint reports text, the matching method of a few key features is better than capturing the global features of the text when judging whether the two complaint reporting tasks are the same origin events. The resolvable attention network decomposed the same-origin complaint reporting task into the matching task between recognition channels, and then judged the relationship between complaint reporting according to the judgment results of each sub-task. This paper compares the accuracy of multiple neural network models on the complaint reporting data set, and the experimental results of these models show that the decomposition of the attention network model in this paper has a better effect and stronger stability. © 2022 Technical Committee on Control Theory, Chinese Association of Automation.

Keyword:

Neural network models

Author Community:

  • [ 1 ] [Zhang, Wangyang]Beijing University of Technology Beijing, Beijing; 100124, China
  • [ 2 ] [Zhang, Wangyang]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 3 ] [Zhang, Wangyang]Beijing Laboratory for Urban Mass Transit, Beijing; 100124, China
  • [ 4 ] [Fan, Qingwu]Beijing University of Technology Beijing, Beijing; 100124, China
  • [ 5 ] [Fan, Qingwu]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 6 ] [Fan, Qingwu]Beijing Laboratory for Urban Mass Transit, Beijing; 100124, China
  • [ 7 ] [Liu, Xudong]Beijing University of Technology Beijing, Beijing; 100124, China
  • [ 8 ] [Sun, Jialin]Beijing University of Technology Beijing, Beijing; 100124, China
  • [ 9 ] [Sun, Jialin]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 10 ] [Sun, Jialin]Beijing Laboratory for Urban Mass Transit, Beijing; 100124, China

Reprint Author's Address:

Email:

Show more details

Related Keywords:

Related Article:

Source :

ISSN: 1934-1768

Year: 2022

Volume: 2022-July

Page: 7197-7202

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

Affiliated Colleges:

Online/Total:743/5409931
Address:BJUT Library(100 Pingleyuan,Chaoyang District,Beijing 100124, China Post Code:100124) Contact Us:010-67392185
Copyright:BJUT Library Technical Support:Beijing Aegean Software Co., Ltd.