Mining Usage Data from Large-Scale Android Users: Challenges and Opportunities

被引：0
|
作者：
Lu, Xuan [1 ]
Liu, Xuanzhe [1 ]
Li, Huoran [1 ]
Xie, Tao [2 ]
Mei, Qiaozhu [3 ]
Hao, Dan [1 ]
Huang, Gang [1 ]
Feng, Feng [4 ]
机构：
[1] Peking Univ, Key Lab High Confidence Software Technol, Minist Educ, Beijing, Peoples R China
[2] Univ Illinois, Champaign, IL USA
[3] Univ Michigan, Ann Arbor, MI 48109 USA
[4] Wandoujia Lab, Beijing, Peoples R China
来源：
2016 IEEE/ACM INTERNATIONAL CONFERENCE ON MOBILE SOFTWARE ENGINEERING AND SYSTEMS (MOBILESOFT 2016) | 2016年
基金：
美国国家科学基金会;
关键词：
Mobile apps; user behavior analysis;
D O I：
10.1145/2897073.2897721
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Mining usage data from a large number of Android users can assist various software engineering tasks. In collaboration with Wandoujia, a leading Android app marketplace in China, we have conducted a large empirical analysis based on mining app usage behaviors collected from millions of Android users. Our empirical findings can provide implications, challenges, and opportunities to app-centric software development, deployment, and maintenance.
引用
收藏
页码：301 / 302
页数：2
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