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Jonathan L. Herlocker
Researcher at Oregon State University
Publications - 39
Citations - 14838
Jonathan L. Herlocker is an academic researcher from Oregon State University. The author has contributed to research in topics: Collaborative filtering & Recommender system. The author has an hindex of 21, co-authored 39 publications receiving 14113 citations. Previous affiliations of Jonathan L. Herlocker include University of Minnesota.
Papers
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Journal ArticleDOI
Evaluating collaborative filtering recommender systems
TL;DR: The key decisions in evaluating collaborative filtering recommender systems are reviewed: the user tasks being evaluated, the types of analysis and datasets being used, the ways in which prediction quality is measured, the evaluation of prediction attributes other than quality, and the user-based evaluation of the system as a whole.
Journal ArticleDOI
GroupLens: applying collaborative filtering to Usenet news
Joseph A. Konstan,Bradley N. Miller,David A. Maltz,Jonathan L. Herlocker,Lee R. Gordon,John Riedl +5 more
TL;DR: The combination of high volume and personal taste made Usenet news a promising candidate for collaborative filtering and the potential predictive utility for Usenets news was very high.
Proceedings ArticleDOI
Explaining collaborative filtering recommendations
TL;DR: This paper presents experimental evidence that shows that providing explanations can improve the acceptance of ACF systems, and presents a model for explanations based on the user's conceptual model of the recommendation process.
Proceedings ArticleDOI
A collaborative filtering algorithm and evaluation metric that accurately model the user experience
TL;DR: It is empirically demonstrated that two of the most acclaimed CF recommendation algorithms have flaws that result in a dramatically unacceptable user experience, and a new Belief Distribution Algorithm is introduced that overcomes these flaws and provides substantially richer user modeling.