OHR:A Hybrid Personalized Recommendation Model Based on Ontology
Zeng Qingfeng · Zhongwen xinxi xuebao · 2010
With the dramatic increase of information available on the Internet,it is obviously a trend to provide users with personalized service.In this paper,through building a generalized service model based on ontology,the Items are classified into service sub-category.and the probability distribution of the users′ interests are calculated.On the basis of the combination of Content Filtering and Item-based Collaborative Filtering,an new ontology-based hybrid personalized recommendation model(OHR) is put forward.The experimental results show that OHR provides the better recommendation results than traditional collaborative filtering algorithms,as well as the better ability to discover the users′ new interests.