Framework for Collaborative Knowledge Sharing and Recommendation Based on Taxonomic Partial Reputations
We propose a novel system for collaborative knowledge sharing and recommendation based on taxonomic partial reputations on web-based personal knowledge directories. And we developed a prototype of the proposed system as a web-based user interface for personal knowledge management. This system presents a personal knowledge directory to a registered user. Such a directory has a personal ontology to integrate and classify the knowledge collected by a user from the Web. And the knowledge sharing activities among registered users generate partial reputation factors of knowledge items, their domain nodes, users and groups. Then new users can obtain the knowledge items proper to their needs, by referring such reputation values of those elements. In addition, users can also take the stem that is a set of common knowledge items over the domains designated by them. Thus proposed system can prevent cold-start problem because our knowledge recommendation mechanisms depend on the results of the collaborative knowledge sharing activities among users.
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