基于超网络的大众协同创新社区用户知识主体挖掘方法研究

如何从海量的、零散的、异质的社区用户知识资源中挖掘出高创新价值的用户知识主体是大数据背景下知识资源挖掘问题的研究热点。本项目围绕着大众协同创新社区中高价值知识主体的挖掘问题展开研究。主要研究内容：（1）基于超网络的大众协同创新社区用户知识系统整合建模方法，通过多种知识网络集成，构建大众协同创新社区用户知识超网络模型；（2）基于用户知识超网络模型，研究面向协同创新需求的用户知识主体挖掘方法，包括用户创新知识社群聚类方法、领先用户识别方法和知识协同者发现方法等。本研究将通过应用实例及原型系统来对模型及方法进行验证。本研究将在大众协同创新社区的用户知识超网络建模和高价值知识主体挖掘方法上取得一定进展。预期成果既是对大众协同创新社区用户知识超网络的理论探索，又是从超网络知识挖掘方法层面上的有益尝试，对知识超网络环境下用户知识资源管理实践有一定的参考价值。

How to discover high value users from the massive, fragmented, heterogeneous user information of virtual communities is a hot research problem of knowledge mining under the age of big data. The project focuses on the mining method of high value knowledge agent in the mass collaborative innovation virtual communities. The research mainly includes: (1) Modeling method for systematic integration of user knowledge of mass collaborative innovation virtual communities based on supernetwork, to build the User Knowledge Supernetwork(UKSN). (2) Mining methods of user knowledge agent for mass collaborative innovation based on UKSN, which include user knowledge community mining method, lead users identification method and knowledge collaborators discovery method. A case study will be conducted to test the proposed methods, and a prototype system will be designed for the project. Breakthroughs can be expected on the model of UKSN and mining methods of high value knowledge agent for the mass collaborative innovation virtual communities. The research findings will help to enrich the theory of USKN for mass collaborative innovation virtual communities, and demonstrate the validity of knowledge mining methods base on superwork, and provide a useful reference for user knowledge resource management practice under the background of knowledge supernetwork.