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In this paper, the authors present an explanation of how recommender systems are related to some traditional database analysis techniques. They examine how recommender systems help E-commerce sites increase sales and analyze the recommender systems at six market-leading sites. Based on these examples, they create taxonomy of recommender systems, including the inputs required from the consumers, the additional knowledge required from the database, the ways the recommendations are presented to consumers, the technologies used to create the recommendations, and the level of personalization of the recommendations. Recommender systems are being used by an ever-increasing number of E-commerce sites to help consumers find products to purchase.
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