Title :
Data Mining Behavioral Transitions in Open Source Repositories
Author :
Robinson, William N. ; Tianjie Deng
Author_Institution :
Comput. Inf. Syst. Dept., Georgia State Univ., Atlanta, GA, USA
Abstract :
Open-source repository data can be automatically mined using sequence mining methods to provide high-level feedback on project status. GitHub.com projects are acquired, sequence-mined, clustered, and regressed to analyze project characteristics. Such results can be presented to project managers, as part of a display generated by an automated monitoring system. Such monitoring systems provide high-level feedback in real-time. This project is a preliminary step in a larger research project aimed at understanding and monitoring FLOSS projects using this process modeling approach.
Keywords :
behavioural sciences computing; data mining; pattern clustering; project management; public domain software; regression analysis; FLOSS projects; GitHub.com projects; automated monitoring system; data clustering; data mining behavioral transitions; high-level feedback; open-source repository data; process modeling approach; project characteristics analysis; project managers; regression analysis; research project; sequence mining methods; Analytical models; Cognition; Data mining; Data models; Hidden Markov models; Monitoring; Software;
Conference_Titel :
System Sciences (HICSS), 2015 48th Hawaii International Conference on
Conference_Location :
Kauai, HI
DOI :
10.1109/HICSS.2015.622
