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Method of Relevance Judgment for App Software’s User Reviews

  • Qixin Xiang
  • Ying JiangEmail author
  • Meng Ran
  • Jiaman Ding
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 728)

Abstract

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.

Keywords

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

Notes

Acknowledgments

This research is sponsored by the National Science Foundation of China Nos. 61462049, 60703116, and 61063006.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Qixin Xiang
    • 1
    • 2
  • Ying Jiang
    • 1
    • 2
    Email author
  • Meng Ran
    • 1
    • 2
  • Jiaman Ding
    • 1
    • 2
  1. 1.Yunnan Key Lab of Computer Technology ApplicationKunmingChina
  2. 2.Faculty of Information Engineering and AutomationKunming University of Science and TechnologyKunmingChina

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