Knowledge Recommendation Services Based on Knowledge Interest Groups

The rapid development of service economy and the continual accumulation of Web knowledge resources provide great opportunities and challenges to global knowledge share and cooperation. Developing virtual community oriented knowledge service systems, providing initiative knowledge services by service providers will be a promising research and practice domain. As the knowledge behavior of community users manifests strong interest preferences, personalized knowledge service, which is provided to community knowledge users, should be knowledge interests oriented. In this paper, we propose a knowledge recommendation services model based on knowledge interest groups in virtual community. In the model, the discovery algorithm of knowledge interest groups based on hot resource sets is presented, and the collaborative knowledge recommendation mechanism, which is based on the computing of the level of knowledge resource´s affection on interest groups, is described