Recommender System Based on Association of Complementary and Similarity in Electronic Market
Majid Khalaji, Seyed Javad Mirabedini, Arak Azad · 2013
Due to developments of Information Technology, most of companies and E-shops are looking for selling their products by the Web. These companies increasingly try to sellproducts and promote their selling strategies by personalization. In this paper, we try to design a Recommender System using association of complementary and similarity among goods and commodities and offer the best goods based on personal needs and interests. We will use of Ontology that can calculate the degree of complementary, the set of complementary products and the similarity, then offer to users. In this paper, we identify two algorithm, CSPAPT and CSPOPT. They have been offer better results in comparison with the algorithm of rules; also they don't have cool start and scalable problems in Recommender Systems.