Journal of Guangxi Normal University(Natural Science Edition) ›› 2011, Vol. 29 ›› Issue (1): 129-132.

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A New Text Classification Approach Based on Fuzzy Soft Set Theory

YUAN Ding-rong1,2, XIE Yang-cai2, LU Guang-quan2, LIU Xing2   

  1. 1.College of Computer Science and Technology,Beijing University of Technology,Beijing 100124,China;
    2.College of Computer Science and Information Technology,Guangxi Normal University,Guilin Guangxi 541004,China
  • Received:2010-12-20 Published:2018-11-16

Abstract: Text classification is one of the key techniques in text information process,which includes how to establish vector model,select feature and train classifier.EIBA and DHCHi2 are integrated to select the features of text and the features are used as parameters in a fuzzy soft set theory.Then a new technique of text classification is established based on a fuzzy softset.Experiments show that the technique is effective,and the ratios of accuracy andrecall are improved comparing with other methods.

Key words: text classification, feature select, Chi2 hapothesis testing, independent degree, fuzzy soft set

CLC Number: 

  • TP391
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