Computer Science ›› 2020, Vol. 47 ›› Issue (12): 56-64.doi: 10.11896/jsjkx.201200031

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Software Requirement Mining Method for Chinese APP User Review Data

WANG Ying, ZHENG Li-wei, ZHANG Yu-yao, ZHANG Xiao-yun   

  1. School of Computer Science Beijing Information Science and Technology University Beijing 100101,China
  • Received:2020-09-03 Revised:2020-10-31 Online:2020-12-15 Published:2020-12-17
  • About author:WANG Ying,born in 1996postgra-duate.Her main research interests include requirement engineering and social networks.
    ZHENG Li-wei,born in 1979Ph.Dassociate professor.His main research interests include requirement engineeringsocial networks and data quality enhancement.
  • Supported by:
    National Natural Science Foundation of China(61402043).

Abstract: Mining requirements from APP user review data is an important way to obtain requirementsbecause users publish reviews of different dimensions of APP in the APP application marketwhich contain many requirements for APP.The APP user review data on the 360 mobile assistant is chosen in our experimentsaiming to discover the software requirements contained in these review data.Firstlythe software requirements contained in APP user review data are divided into five categorieswhich include functions to be addedfunctions to be improvedperformanceavailabilityand reliability.Secondlydata collectionlabeling of user comments and constructing app review requirements mining data set are carried on.Finallythe constructed data set is used for model training and testing to explore the performance of deep learning methods compared with statistical machine lear-ning models on this task.The experiment results show that the deep learning modelsTextCNNTextRNNand Transformer used in this paperhave more advantages in this task than traditional statistical machine learning models.

Key words: APP user reviews, Software requirements mining, Machine learning, Chinese data set

CLC Number: 

  • TP311
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