Research on Web Recommendation Method Based on Tags and Deep Ontology
Zheng Chen · Jisuanji gongcheng · 2015
Based on users' likings of items and their browsing history on the world wide Web,recommendation systems are able to predict and recommend items and future purchases to users.However,sparse and cold start problems influence the effect of this approach.This paper proposes a method of Web recommendationsystem based on tags and deep ontology.Through using deep ontology relations and tags marked by the users,a dimensionality reduction method based on the deep ontology is proposed,and click stream is mapped on ontology,and top-n recommendations are provided.Experimental result shows that the method for sparse and cold starting problems has a more obvious improvement,recommendation accuracy and timeliness have better results than traditional methods based on ontology.