Noise control in document classification based on fuzzy formal concept analysis

Sheng-Tun Li, Fu Ching Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Document classification is critical due to explosive increasing of text in modern world. However, most of existing document classification algorithms are easily affected by noise data. Therefore, in document classification tasks, the ability of noise control is as important as the ability to classify exactly. In this paper, we propose a novel classification framework based on fuzzy formal concept analysis to moderate the impact from noise. In addition, the well-organized concepts also provide inherent relations, which support knowledge codification and distribution effectively. Experimental results using Reuters 21578 dataset demonstrates significant noise control benefit and superior classification accuracy.

Original languageEnglish
Title of host publicationFUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Pages2583-2588
Number of pages6
DOIs
Publication statusPublished - 2011 Sep 27
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
Duration: 2011 Jun 272011 Jun 30

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Other

Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
CountryTaiwan
CityTaipei
Period11-06-2711-06-30

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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