Incorporating task-oriented representation in text classification

Xue Lei, Yi Cai, Jingyun Xu, Da Ren, Qing Li, Ho fung Leung

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


Text classification (TC) is an important task in natural language processing. Recently neural network has been applied to text classification and achieves significant improvement in performance. Since some documents are short and ambiguous, recent research enriches document representation with concepts of words extracted from an external knowledge base. However, this approach might incorporate task-irrelevant concepts or coarse granularity concepts that could not discriminate classes in a TC task. This might add noise to document representation and degrade TC performance. To tackle this problem, we propose a task-oriented representation that captures word-class relevance as task-relevant information. We integrate task-oriented representation in a CNN classification model to perform TC. Experimental results on widely used datasets show our approach outperforms comparison models.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Proceedings
EditorsGuoliang Li, Jun Yang, Joao Gama, Juggapong Natwichai, Yongxin Tong
Number of pages15
ISBN (Print)9783030185787
Publication statusPublished - 1 Jan 2019
Event24th International Conference on Database Systems for Advanced Applications, DASFAA 2019 - Chiang Mai, Thailand
Duration: 22 Apr 201925 Apr 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11447 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference24th International Conference on Database Systems for Advanced Applications, DASFAA 2019
CityChiang Mai


  • Natural language processing
  • Neural network
  • Text classification

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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