Transcription of Industry Report Amazon.com Recommendations
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Industry Report Amazon.com Recommendations
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.
tomer base. The complex and expensive clustering computation is run offline. However, recommen-dation quality is low.1 Cluster models group numerous customers together in a segment, match
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