Abstract

With current projections regarding the growth of Internet sales, online retailing raises many questions about how to market on the Net. While convenience impels consumers to purchase items on the web, quality remains a significant factor in deciding where to shop online. The competition is increasing and personalization is considered to be the competitive advantage that will determine the winners in the market of online shopping in the following years. Recommender systems are a means of personalizing a site and a solution to the customer’s information overload problem. As such, many e-commerce sites already use them to facilitate the buying process. In this paper we study the application of recommender systems for electronic retail sites, focusing on the peculiar characteristics and requirements of this environment. We also introduce a hybrid model supporting dynamic recommendations, which eliminates the problems the underlying techniques have when applied solely. We then discuss the application of the proposed solution in the case of an innovative research project on electronic retailing funded by the European Commission and conclude with some ideas for further development and research in this area.

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