Mining usage data from large-scale android users: Challenges and opportunities

Xuan Lu, Xuanzhe Liu, Huoran Li, Tao Xie, Qiaozhu Mei, Dan Hao, Gang Huang, Feng Feng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Mobile Software Engineering and Systems, MOBILESoft 2016
PublisherAssociation for Computing Machinery
Pages301-302
Number of pages2
ISBN (Electronic)9781450341783
DOIs
StatePublished - May 14 2016
EventIEEE/ACM International Conference on Mobile Software Engineering and Systems, MobileSoft 2016 - Austin, United States
Duration: May 16 2016May 17 2016

Publication series

NameProceedings - International Conference on Mobile Software Engineering and Systems, MOBILESoft 2016

Other

OtherIEEE/ACM International Conference on Mobile Software Engineering and Systems, MobileSoft 2016
Country/TerritoryUnited States
CityAustin
Period5/16/165/17/16

Keywords

  • Mobile apps
  • User behavior analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications
  • Signal Processing

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