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Improving Recommender Systems in E-Commerce Using Similar Goods

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Author(s): S. Javad Mirabedini | Keramat Mansouri | Majid Khalaji

Journal: Advances in Molecular Imaging
ISSN 2161-6728

Volume: 05;
Issue: 02;
Start page: 96;
Date: 2012;
Original page

Keywords: Recommender System | Ontology | Similarity | Complementary | Association Rule | Collaborative Filtering

ABSTRACT
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 sell products 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 ontology that can calculate the degree of complementary, the set of complementary products and the similarity, and then offer them to users. In this paper, we identify two algorithms, CSPAPT and CSPOPT. They have offered better results in comparison with the algorithm of rules; also they don’t have cool start and scalable problems in Recommender Systems.
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Tango Rapperswil
Tango Rapperswil