Collaborative Filtering Recommender Systems

MDMichael D. EkstrandJTJohn T. RiedlJAJoseph A. Konstan

University of Minnesota

Indexed incrossref

Abstract

Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly two decades of research on collaborative filtering have led to a varied set of algorithms and a rich collection of tools for evaluating their performance. Research in the field is moving in the direction of a richer understanding of how recommender technology may be embedded in specific domains. The differing personalities exhibited by different recommender algorithms show that recommendation is not a one-size-fits-all problem. Specific tasks, information needs, and item domains represent unique problems for…

Citation impact

1,016
total citations
FWCI
62.65
Percentile
100%
References
151
Citations per year

Authors

3

Topics & keywords

Keywords
  • Recommender system
  • Collaborative filtering
  • Computer science
  • Information retrieval
  • World Wide Web
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