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New Methods for Text Categorization Based on a New Feature Selection Method and a New Similarity Measure Between Documents

  • Li-Wei Lee
  • Shyi-Ming Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4031)

Abstract

In this paper, we present a new feature selection method based on document frequencies and statistical values. We also present a new similarity measure to calculate the degree of similarity between documents. Based on the proposed feature selection method and the proposed similarity measure between documents, we present three methods for dealing with the Reuters-21578 top 10 categories text categorization. The proposed methods get higher performance for dealing with the Reuters-21578 top 10 categories text categorization than that of the method presented in [4].

Keywords

Feature Selection Mutual Information Testing Document Feature Selection Method Text Categorization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Li-Wei Lee
    • 1
  • Shyi-Ming Chen
    • 1
  1. 1.Department of Computer Science and Information EngineeringNational Taiwan University of Science and TechnologyTaipeiTaiwan, R.O.C.

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