Computer Science ›› 2016, Vol. 43 ›› Issue (9): 82-86.doi: 10.11896/j.issn.1002-137X.2016.09.015

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Research on Effect of Adding Internal Semantic Relationship into Text Categorization

ZHU Jian-lin, YANG Xiao-ping and PENG Jing-qiao   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In order to improve the effect of text categorization on the premise of no addition of the external knowledge,this paper presented a feature matrix-based categorization framework.First,the internal knowledge of corpus is mined and added into the original word-text matrix in different ways.Two common algorithms named SVM and KNN are chosen for contrastive experiment of text categorization in highly territorial legal corpus and domain-wide news corpus.Experi-mental results show that it is generally helpful when adding the semantic relationships extracted from corpus into the original matrix,but the adding method should be chosen according to different classification methods and domain chara-cteristics.

Key words: Vector space model,Text categorization,Semantic mining,Feature matrix

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