一种多特征融合的软件开发者推荐

软件开发者能力评价和协作关系推荐是大数据环境下软件智能化开发领域的一个研究热点.通过分析互联网开发者社区和企业内部开发环境，设计出基于模糊综合评价的开发者能力模型；随后，通过挖掘开发者与任务的动态交互行为、静态匹配度以及开发者能力三个不同维度的特征并结合矩阵分解技术，提出一种能力与行为感知的多特征融合协同过滤开发者推荐方法，最终解决开发者推荐面临的评价矩阵稀疏性和冷启动问题，提升个性化精准推荐效率.从系统层面给出适合大数据环境的多特征融合开发者推荐原型系统实践及对现有开源技术框架的优化改进，实验过程分别基于互联网问答社区StackOverflow和企业内部GitLab环境进行了实验分析.最后，对未来研究可能的问题及思路进行了展望.

Multi-Feature Fused Software Developer Recommendation

The capability evaluation and collaborative relationship recommendation of software developers is a hot topic in the field of software intelligent development in large data environment. By analyzing the Internet developer community and the enterprise internal development environment, the author designs the developer ability model based on fuzzy comprehensive evaluation. Subsequently, the three different dimensions of the dynamic interaction behavior, static matching, and developer capabilities are extracted by mining the dynamic interaction between the developer and the task, combining matrix decomposition techniques, a multi-feature fusion enhanced method based on capability and behavior for collaborative filtering developer recommendation is proposed, and ultimately solve the evaluation matrix sparseness and cold start problem of developer recommendation, enhance the personalized precision recommended efficiency. From the aspect of system, a prototype system of multi feature fusion recommendation system suitable for large data environment is presented, and the optimization of existing open source technology framework is improved. The experiment is based on the Internet Q&A community StackOverflow and the internal GitLab environment of the enterprise. Finally, the possible problems and ideas for future research are prospected.