Personalized Knowledge Recommendation in Digital Library Based on Semantic-Expansion
Zhang Dong-mei · Journal of North University of China · 2008
Personalized knowledge recommendation is an effective means to provide individual information service in digital library,however,a complete understanding of the user profile and accurate recommendation are essential.In this paper,the method adopts a semantic-expansion approach to build the user profile by analyzing documents previously read by the person,matching keywords of the documents and the concepts in the expanded user profile,rating documents in database and making recommendation.The profile of user interest is then dynamic renewal from the relevance feedback.