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Method of Relevance Judgment for App Software’s User Reviews

     

摘要

In order to judge whether the user reviews are relevant to App software, this paper proposed a method to judge the relevance of user reviews based on Naive Bayesian text classification and term frequency.Firstly, the keywords sets of App software’s user reviews are extracted. Then, the keywords sets are optimized. Finally, the relevance score of the user reviews are calculated, and whether the user reviews are relevant is judged. Through the experiment, this method is proved that can judge the relevance of App software’s user reviews effectively.

著录项

  • 来源
  • 作者单位

    [1]Yunnan Key Lab of Computer Technology Application, Kunming 650500, China;

    [2]Faculty of Information Engineering and Automation,Kunming University of Science and Technology, Kunming 650500, China;

    [1]Yunnan Key Lab of Computer Technology Application, Kunming 650500, China;

    [2]Faculty of Information Engineering and Automation,Kunming University of Science and Technology, Kunming 650500, China;

    [1]Yunnan Key Lab of Computer Technology Application, Kunming 650500, China;

    [2]Faculty of Information Engineering and Automation,Kunming University of Science and Technology, Kunming 650500, China;

    [1]Yunnan Key Lab of Computer Technology Application, Kunming 650500, China;

    [2]Faculty of Information Engineering and Automation,Kunming University of Science and Technology, Kunming 650500, China;

  • 原文格式 PDF
  • 正文语种 CHI
  • 中图分类 实验室和设备;
  • 关键词

    App software; User reviews; Relevance judgment; Naive Bayesian text classification; Term frequency;

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