articleAI MagazineSep 1, 2011BRONZE OA

Context‐Aware Recommender Systems

GAGediminas AdomavičiusBMBamshad MobasherFRFrancesco Ricci⋆ATAlex Tuzhilin

University of Minnesota · University of Minnesota System · +3 more institutions

Indexed incrossref

Abstract

Context‐aware recommender systems (CARS) generate more relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create intelligent and useful recommender systems. It provides an overview of the multifaceted notion of context, discusses several approaches for incorporating contextual information in the recommendation process, and illustrates the usage of such approaches in several application areas where different types of contexts are exploited. The article concludes by discussing the challenges and future research directions for context‐aware recommender systems.

Citation impact

1,363
total citations
FWCI
280.38
Percentile
100%
References
90
Citations per year

Authors

4

Topics & keywords

Topics
Keywords
  • Recommender system
  • Computer science
  • Context (archaeology)
  • Process (computing)
  • World Wide Web
  • Data science
  • Information retrieval
  • Human–computer interaction
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