Recommender System Based on Semantic Similarity and Collaborative Filtering

摘要

To enable semantics based on recommender systems, products and user profiles need to be represented in knowledge uniformly where ontology can be exploited. User profile modeling approach is proposed in this paper. The method of implicit rating and weight evaluation of product attributes is explored. A hybrid approach combining semantic similarity with collaborative filtering is proposed to generate the recommendation lists for users.