Explaining collaborative filtering recommendations

Proceedings of the ACM Conference on Computer Supported Cooperative Work

Volumn , Issue , 2000, Pages 241-250

  Herlocker, J L ^a   Konstan, J A ^a   Riedl, J ^a  

^a University of Minnesota   (United States)

Author keywords

Collaborative filtering; Explanations; GroupLens; MovieLens; Recommender systems

Indexed keywords

DATA STRUCTURES; ERRORS; GRAPH THEORY; GROUPWARE; MATHEMATICAL MODELS;

AUTOMATED COLLABORATIVE FILTERING SYSTEM; BLACK BOX; GROUPLENS; MOVIELENS; RECOMMENDER SYSTEM;

USER INTERFACES;

EID: 0034446870     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/358916.358995     Document Type: Conference Paper

References (14)

1. Jump-starting movielens: User benefits of starting a collaborative filtering system with "dead data"
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3. Recommending and evaluating choices in a virtual community of use
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5. Explanation facilities and interactive systems
6. GroupLens: Applying collaborative filtering to usenet news
7. An explanatory and "argumentative" interface for a model-based diagnostic system
8. GroupLens: An open architecture for collaborative filtering of netnews
9. Social information filtering: Algorithms for automating "Word of Mouth"