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GROUPLENS COLLABORATIVE FILTERING RECOMMENDER SYSTEMS
https://awards.acm.org/award_winners/riedl_2663490

Explaining Collaborative Filtering Recommendations

Jonathan L. Herlocker, Joseph A. Konstan, and John Riedl
https://grouplens.org/site-content/uploads/explain-CSCW-20001.pdf

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  4. Dahlen,B.J., Konstan,J.A., Herlocker,J.L., Good,N., Borchers,A., Riedl,J., 1998. Jump-starting movielens: User benefits of starting a collaborative filtering system with "dead data". University of Minnesota TR 98-017.
  5. Herlocker,J.L., Konstan,J.A., Borchers,A., Riedl,J., 1999. An algorithmic framework for performing collaborative filtering. Proceedings of the 1999 Conference on Research and Development in Information Retrieval.
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Evaluating Collaborative Filtering Recommender Systems

JONATHAN L. HERLOCKER Oregon State University nd JOSEPH A. KONSTAN, LOREN G. TERVEEN, and JOHN T. RIEDL University of Minnesota
https://grouplens.org/site-content/uploads/evaluating-TOIS-20041.pdf

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Received January 2003; revised June 2003; accepted August 2003

arXiv

Learning with Linear Mixed Model for Group Recommendation Systems

Baode Gao, Guangpeng Zhan, Hanzhang Wang, Yiming Wang, Shengxin Zhu
https://arxiv.org/pdf/2212.08901

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