Multiple Sets of Rules for Text Categorization

  • Yaxin Bi
  • Terry Anderson
  • Sally McClean
Conference paper

DOI: 10.1007/978-3-540-30198-1_27

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3261)
Cite this paper as:
Bi Y., Anderson T., McClean S. (2004) Multiple Sets of Rules for Text Categorization. In: Yakhno T. (eds) Advances in Information Systems. ADVIS 2004. Lecture Notes in Computer Science, vol 3261. Springer, Berlin, Heidelberg

Abstract

This paper concerns how multiple sets of rules can be generated using a rough sets-based inductive learning method and how they can be combined for text categorization by using Dempster’s rule of combination. We first propose a boosting-like technique for generating multiple sets of rules based on rough set theory, and then model outcomes inferred from rules as pieces of evidence. The various experiments have been carried out on 10 out of the 20-newsgroups – a benchmark data collection – individually and in combination. Our experimental results support the claim that “k experts may be better than any one if their individual judgements are appropriately combined”.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Yaxin Bi
    • 1
    • 2
  • Terry Anderson
    • 3
  • Sally McClean
    • 3
  1. 1.School of Computer ScienceQueen’s University of BelfastBelfastUK
  2. 2.School of Biomedical ScienceUniversity of UlsterColeraine, LondonderryUK
  3. 3.Faculty of EngineeringUniversity of UlsterNewtownabbey, Co. AntrimUK

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