An algorithmic framework for performing collaborative filtering

Jonathan L. Herlocker, Joseph A Konstan, Al Borchers, John Riedl

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2058 Scopus citations

Abstract

Automated collaborative filtering is quickly becoming a popular technique for reducing information overload, often as a technique to complement content-based information filtering systems. In this paper we present an algorithmic framework for performing collaborative filtering and new algorithmic elements that increase the accuracy of collaborative prediction algorithms. We then present a set of recommendations on selection of the right collaborative filtering algorithmic components.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999
PublisherAssociation for Computing Machinery, Inc
Pages230-237
Number of pages8
ISBN (Electronic)1581130961, 9781581130966
DOIs
StatePublished - Aug 1 1999
Event22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999 - Berkeley, United States
Duration: Aug 15 1999Aug 19 1999

Publication series

NameProceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999

Other

Other22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999
CountryUnited States
CityBerkeley
Period8/15/998/19/99

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