A Contextual Similarity Recommendation Algorithm Based on Ontology Semantic

Abstract

This paper considers an contextual similarity recommendation algorithm based on ontology semantic which recommends commodities to users by the similarity between current user's context and source context recorded. First, We divide the context ontology tree into many sub trees with sub tree cutting algorithm. According to calculating the similarity of sub trees with the weight sum, we obtain the similarity between the source context and target context. Meanwhile, during calculating the similarity of sub trees, this paper allows for ontology semantic similarity, and adds the structure similarity degree algorithm on the basis of the old ontology similarity degree algorithm, which makes the result more accord with actual, and finally the experiment is verified.