Mining user requirements to facilitate mobile app quality upgrades with big data

被引：29

作者：

Chen, Runyu ^{[1
]}

Wang, Qili ^{[1
]}

Xu, Wei ^{[1
]}

机构：

[1] Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China

来源：

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS | 2019年 / 38卷

基金：

中国国家自然科学基金;

关键词：

User requirements; Product upgrades; Data mining; Text analytics; Mobile apps; REVIEWS; DETERMINANTS; IMPROVEMENT; ONTOLOGY;

D O I：

10.1016/j.elerap.2019.100889

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

A domain-dependent customer requirements mining framework to facilitate mobile app quality upgrades is proposed in this paper. We develop a new ranking model to rank the importance of different customer requirements by considering both the rating data and review data. We prove the effectiveness in terms of product quality improvements based on 265 version update cases for 15 popular mobile apps. As there is little research regarding identifying the business value of customer requirements mining, this study can be highly beneficial to the further development of research concerning the business value of adopting online customer requirements for product improvements.

引用

页数：11

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