Explanation for Recommender Systems: Satisfaction vs. Promotion
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[1] Edward H. Shortliffe,et al. Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence) , 1984 .
[2] Mark Rosenstein,et al. Recommending and evaluating choices in a virtual community of use , 1995, CHI '95.
[3] Mark Claypool,et al. Combining Content-Based and Collaborative Filters in an Online Newspaper , 1999, SIGIR 1999.
[4] Michael J. Pazzani,et al. Syskill & Webert: Identifying Interesting Web Sites , 1996, AAAI/IAAI, Vol. 1.
[5] John Riedl,et al. An algorithmic framework for performing collaborative filtering , 1999, SIGIR '99.
[6] Bradley N. Miller,et al. MovieLens unplugged: experiences with an occasionally connected recommender system , 2003, IUI '03.
[7] Paul Resnick,et al. Recommender systems , 1997, CACM.
[8] Ken Lang,et al. NewsWeeder: Learning to Filter Netnews , 1995, ICML.
[9] John Riedl,et al. GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.
[10] Pattie Maes,et al. Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.
[11] Yoav Shoham,et al. Fab: content-based, collaborative recommendation , 1997, CACM.
[12] Christian Posse,et al. Bayesian Mixed-Effects Models for Recommender Systems , 1999 .
[13] Loriene Roy,et al. Content-based book recommending using learning for text categorization , 1999, DL '00.
[14] William W. Cohen,et al. Recommendation as Classification: Using Social and Content-Based Information in Recommendation , 1998, AAAI/IAAI.
[15] Michael J. Pazzani,et al. A personal news agent that talks, learns and explains , 1999, AGENTS '99.
[16] Bradley N. Miller,et al. Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system , 1998, CSCW '98.
[17] Raymond J. Mooney,et al. Content-boosted collaborative filtering for improved recommendations , 2002, AAAI/IAAI.
[18] John Riedl,et al. Explaining collaborative filtering recommendations , 2000, CSCW '00.