Users’ Comment Mining for App Software’s Quality-in-Use

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1042)


Only parts of app software users’ comments reflect software quality-in-use. A large number of useless users’ comments will affect the analysis of software quality-in-use. In order to mine the users’ comments about the quality-in-use from the massive app software users’ comments, a mining method of users’ comments based on comment seed is proposed. At first, the users’ comments reflecting the app software’s quality-in-use are mined through initial comment seeds. For the comments that cannot be matched with the comment seed, it will be determined whether they reflect quality-in-use according to the app software’s quality-in-use feature words. Then, the candidate comment modes are extracted from the comments that can be matched with the app software’s quality-in-use feature words. The new comment seeds are extracted based on the candidate comment mode library to further mine the users’ comments related to the quality-in-use. Finally, the experimental results show that the proposed method can effectively mine users’ comments reflecting app software quality-in-use with an average mining rate of 79.49%.


App software Quality-in-Use Comment mining Comment seed Comment mode 



This research is sponsored by the National Science Foundation of China No. 61462049, 60703116, and 61063006, Key Project of Yunnan Applied Basic Research No. 2017FA033 and the Scientific Research Fund Project of the Yunnan Education Department No. 2018Y016.


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Yunnan Key Lab of Computer Technology ApplicationKunming University of Science and TechnologyKunmingChina
  2. 2.Faculty of Information Engineering and AutomationKunming University of Science and TechnologyKunmingChina

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