A Comparison of Collaborative-Filtering Recommendation Algorithms for E-commerce
IEEE Intelligent SystemsPublished 1 September 2007
Zan Huang, Daniel Zeng, Hsinchun Chen
Citations193
SJR quartileQ1
SJR score1.33
SNIP2.01
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TL;DR
Researchers are advancing CF technologies in such areas as algorithm design, human- computer interaction design, consumer incentive analysis, and privacy protection.
Abstract
Collaborative filtering is one of the most widely adopted and successful recommendation approaches. Unlike approaches based on intrinsic consumer and product characteristics, CF characterizes consumers and products implicitly by their previous interactions. The simplest example is to recommend the most popular products to all consumers. Researchers are advancing CF technologies in such areas as algorithm design, human- computer interaction design, consumer incentive analysis, and privacy protection.
Keywords
Computer ScienceBusiness, Management and AccountingSocial Sciences
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