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 language | English (US) |
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Title of host publication | Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999 |
Publisher | Association for Computing Machinery, Inc |
Pages | 230-237 |
Number of pages | 8 |
ISBN (Electronic) | 1581130961, 9781581130966 |
DOIs | |
State | Published - Aug 1 1999 |
Event | 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999 - Berkeley, United States Duration: Aug 15 1999 → Aug 19 1999 |
Publication series
Name | Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999 |
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Other
Other | 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 1999 |
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Country/Territory | United States |
City | Berkeley |
Period | 8/15/99 → 8/19/99 |
Bibliographical note
Publisher Copyright:Copyright 1999 ACM.