Transcription of Industry Report Amazon.com Recommendations - UMD
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Industry Report76 JANUARY FEBRUARY 2003 Published by the IEEE Computer Society1089-7801/03/$ 2003 IEEEIEEE INTERNET Item-to-Item Collaborative FilteringRecommendation algorithms are bestknown for their use on e-commerce Websites,1where they use input about a cus-tomer s interests to generate a list of recommend-ed items. Many applications use only the itemsthat customers purchase and explicitly rate to rep-resent their interests, but they can also use otherattributes, including items viewed, demographicdata, subject interests, and favorite artists. At , we use recommendation algo-rithms to personalize the online store for each cus-tomer.
Figure 1. The “Your Recommendations”feature on the Amazon.com homepage.Using this feature,customers can sort recommendations and add their own product ratings. Figure 2. Amazon.com shopping cart recommendations. The recom-mendations are based on the items in the customer’s cart: The Pragmatic Programmer and Physics for Game Developers.
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