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An Algorithmic Framework for Performing Collaborative Filtering
Abstract
column Share on An Algorithmic Framework for Performing Collaborative Filtering Authors: Jonathan L. Herlocker University of Minnesota University of MinnesotaView Profile , Joseph A. Konstan University of Minnesota University of MinnesotaView Profile , Al Borchers University of Minnesota University of MinnesotaView Profile , John Riedl University of Minnesota University of MinnesotaView Profile Authors Info & Claims ACM SIGIR ForumVolume 51Issue 2July 2017 pp 227–234https://doi.org/10.1145/3130348.3130372Published:02 August 2017Publication History 63citation823DownloadsMetricsTotal Citations63Total Downloads823Last 12 Months45Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
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- ACM. Special issue on information filtering. Gommunciations of the ACM, 35(12) , December 1992 . ACM. Special issue on information filtering. Gommunciations of the ACM, 35(12), December 1992.
- 10.1145/245108.245124 · DOI · Paper page
- Chumki Basu , Haym Hirsh , and William Cohen . Recommendation as classification: using social and content-based information in recommendation . In Proceedings of the 1998 Workshop on Recommender Systems , pages 11 - 15 . AAAI Press , August 1998 . Chumki Basu, Haym Hirsh, and William Cohen. Recommendation as classification: using social and content-based information in recommendation. In Proceedings of the 1998 Workshop on Recommender Systems, pages 11-15. AAAI Press, August 1998.
- Daniel Billsus and Michael J. Pazzani . Learning collaborative information filters . In Proceedings of the 1998 Workshop on Recommender Systems. AAAI Press , August 1998 . Daniel Billsus and Michael J. Pazzani. Learning collaborative information filters. In Proceedings of the 1998 Workshop on Recommender Systems. AAAI Press, August 1998.
- John S. Breese , David Heckerman , and Carl Kadie . Empirical analysis of predictive algorithms for collaborative filtering . In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98) , pages 4352 , San Francisco , July 24-26 1998 . John S. Breese, David Heckerman, and Carl Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98), pages 4352, San Francisco, July 24-26 1998.
- 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9 · DOI
- 10.1145/138859.138867 · DOI · Paper page
- 10.1145/223904.223929 · DOI · Paper page
- 10.1145/245108.245123 · DOI · Paper page
- 10.1145/245108.245126 · DOI · Paper page
- 10.1145/176789.176792 · DOI · Paper page
- 10.1145/223904.223930 · DOI
- James T. McClave and Frank H . Dietrich II. Statistics . Dellen Publishing Company , 1988 . James T. McClave and Frank H. Dietrich II. Statistics. Dellen Publishing Company, 1988.
- 10.5555/188490.188583 · doi:10.5555/188490.188583
- 10.5555/6771 · doi:10.5555/6771
- 10.1145/192844.192905 · DOI · Paper page
- 10.1207/s15516709cog0304_3 · DOI · Paper page
- 10.1016/0306-4573(88)90021-0 · DOI · Paper page
- 10.1145/289444.289509 · DOI · Paper page
- 10.1145/223904.223931 · DOI · Paper page
- 10.1126/science.3287615 · DOI · Paper page
- 10.1145/245108.245122 · DOI · Paper page
- C. J. van Rijsbergen . Information Retrieval , chapter 7. Butterworths , 1979 . C. J. van Rijsbergen. Information Retrieval, chapter 7. Butterworths, 1979.
- 10.5555/857186.857579 · doi:10.5555/857186.857579
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Metadata
- Authors
- Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J.
- Venue
- ACM SIGIR Forum
- Published
- 2017-08-02
- Volume
- 51
- Issue
- 2
- Pages
- 227-234
- ISSN
- 0163-5840 (ISSN-L)
- OpenAlex
- W2085937320
- Cited by
- 2,512
- References
- 0
- FWCI
- 219.05
- Type
- journal article
- Language
- en
- Open access
- closed
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