Recommender systems: from algorithms to user experience

@article{Konstan2011RecommenderSF,
  title={Recommender systems: from algorithms to user experience},
  author={J. Konstan and J. Riedl},
  journal={User Modeling and User-Adapted Interaction},
  year={2011},
  volume={22},
  pages={101-123}
}
  • J. Konstan, J. Riedl
  • Published 2011
  • Computer Science
  • User Modeling and User-Adapted Interaction
Since their introduction in the early 1990’s, automated recommender systems have revolutionized the marketing and delivery of commerce and content by providing personalized recommendations and predictions over a variety of large and complex product offerings. In this article, we review the key advances in collaborative filtering recommender systems, focusing on the evolution from research concentrated purely on algorithms to research concentrated on the rich set of questions around the user… Expand
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This paper proposes a framework that takes a user-centric approach to recommender system evaluation that links objective system aspects to objective user behavior through a series of perceptual and evaluative constructs (called subjective system aspects and experience, respectively). Expand
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TLDR
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