
A Research Review of Mobile Application Review Mining
Zhang Ji, Kang Lele, Li Bo
Knowledge Management Forum ›› 2021, Vol. 6 ›› Issue (6) : 339-350.
A Research Review of Mobile Application Review Mining
[Purpose/significance] User reviews are helpful for developers to realize mobile application innovation. This paper summarizes the literature related to mobile application review mining and provides references for mobile application development and review mining. [Method/process] This study reviewed the researches related to mobile application review mining into three key themes of review classification, review clustering and review feature extraction by using the text analysis method, and expounded on the development status of this field according to this framework. [Result/conclusion] At present, the methods of review classification have begun to evolve from machine learning to deep learning; review clustering mainly uses K-Means and DBSCAN; feature extraction is still focused on the explicit features of APP reviews. In the future, there are still three issues worth exploring in mobile application review mining: domain dependence, multi-source information fusion and review value evaluation.
mobile application / review mining / review classification / review clustering / feature extraction
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张季:撰写论文初稿;
康乐乐:提出研究选题,调整论文框架,修改论文;
李博:修改论文。
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