GroupLens | RDL Research Database

Abstract

Collaborative filters help people make choices based on the opinions of other people. GroupLens is a system for collaborative filtering of netnews, to help people find articles they will like in the huge stream of available articles. News reader clients display predicted scores and make it easy for users to rate articles after they read them. Rating servers, called Better Bit Bureaus, gather and disseminate the ratings. The rating servers predict scores based on the heuristic that people who agreed in the past will probably agree again. Users can protect their privacy by entering ratings under pseudonyms, without reducing the effectiveness of the score prediction. The entire architecture is open: alternative software for news clients and Better Bit Bureaus can be developed independently and can interoperate with the components we have developed.

Keywords

Computer scienceCollaborative filteringInteroperabilityServerDisseminationWorld Wide WebInternet privacyRecommender systemTelecommunications

Affiliated Institutions

University of Minnesota US

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Publication Info

Year: 1994
Type: article
Pages: 175-186
Citations: 4960
Access: Closed

External Links

View on DOI.org

Social Impact

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GroupLens

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Social media, news, blog, policy document mentions

Citation Metrics

4960

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Cite This

APA Style

                            
                                    Paul Resnick, 
                                
                                    Neophytos Iacovou, 
                                
                                    Mitesh Suchak
                                
                                et al.
                            
                            (1994). 
                            GroupLens. 
                            
                            , 175-186.
                            https://doi.org/10.1145/192844.192905

Identifiers

DOI: 10.1145/192844.192905