微信服务号

微信订阅号

2025-4-21- 18
Home > Archive>Volume 28, Issue 6, 2017 >1357-1372. DOI:10.13328/j.cnki.jos.005230
PDF HTML XML Export Cite reminder
Multi-Feature Based Personal Recommendation Approach for Open Source Project
Author:
Affiliation:

Fund Project:

National Natural Science Foundation of China (61432020, 61472430, 61502512); National Key Research and Development Program (2016YFB1000805)

  • Article
    • | |
  • Metrics
    • |
  • Reference
    • |
  • Related
    • |
  • Cited by
    • | |
  • Comments
    Abstract:

    With the deep integration of software collaborative development and social networking, social coding represents a new style of software production and creation paradigm. Due to the flexibility and openness, a large number of external contributors are attracted to the open source communities. They are playing a significant role in open source development. However, the online open source development is a globalized and distributed cooperative work. If left unsupervised, the contribution process may result in inefficiency. It takes contributors a lot of time to find suitable projects or tasks to work on from thousands of open source projects in the communities. In this paper, a new approach, called RepoLike, is proposed for recommending repositories to developers based on linear combination and learning to rank. It utilizes the project popularity, technical dependencies among projects and social connections among developers to measure the correlations between a developer and the given projects. The experiment results show that this new approach can achieve over 25% of hit ratio when recommending 20 candidates, which means it can recommend closely correlated repositories to social developers.

    Reference
    Related
    Cited by
Get Citation

杨程,范强,王涛,尹刚,王怀民.基于多维特征的开源项目个性化推荐方法.软件学报,2017,28(6):1357-1372

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:October 17,2016
  • Revised:October 26,2016
  • Online: February 21,2017
Links:Institute of Software, CASChina Computer FederationCASNSFC
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address：4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code：100190
Phone：010-62562563 Fax：010-62562533 Email：jos@iscas.ac.cn
Technical Support：Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063