An Algorithm for Goods Implicit Rating based on Web Pages Semantic Similarity
基于网页语义相似性的商品隐性评分算法

On the basis of analyzing the recommendation system of e-commerce and algorithm existing problem at present,recommend algorithms,and put forward a kind of accurate implicit Rating approach based on Web Pages Semantic Similarity.By exploiting goods knowledge distributed in different Web pages,a CA(Goods Concpet-Attribute Matrix) model was structured which combines goods attributes,related goods and those distribution.Using thesaurus(e.g.,WordNet) to calculate the Semantic Similarity of Web pages of the user's current access path,a semantics-based implicit rating model was presented in this paper.An example of calculating process was showed.Experimental evaluation demonstrated this approach was more accurate than traditional Implicit Rating algorithms.