A method for chinese text classification based on three-dimensional vector space model

Jixian Zhang*, Qinglin Wang, Yuan Li, Dongmei Li, Yuexing Hao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Text classification is an important research direction of text mining and the research of Chinese text automatic classification is also becoming a research focus of intelligent classification. Against the particularity of the Chinese text classification, this paper presents a three-dimensional vector space model on the basis of the vector space model to improve the accuracy and efficiency of text classification. Experimental results show that the accuracy rate increased to 98.8125% which proves that the algorithm is effective.

Original languageEnglish
Title of host publicationProceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012
Pages1324-1327
Number of pages4
DOIs
Publication statusPublished - 2012
Event2012 International Conference on Computer Science and Service System, CSSS 2012 - Nanjing, China
Duration: 11 Aug 201213 Aug 2012

Publication series

NameProceedings - 2012 International Conference on Computer Science and Service System, CSSS 2012

Conference

Conference2012 International Conference on Computer Science and Service System, CSSS 2012
Country/TerritoryChina
CityNanjing
Period11/08/1213/08/12

Keywords

  • SVM
  • feature vector
  • field dictionary
  • statistical methods
  • text classificaiton

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