Abstract
Collaborative ltering attempts to alleviate in- formation overload by o ering recommenda- tions on whether information is valuable based on the opinions of those who have already eval- uated it. Usenet news is an information source whose value is being severely diminished by the volume of low-quality and uninteresting infor- mation posted in its newsgroups. The Grou- pLens system applies collaborative ltering to Usenet news to demonstrate how we can re- store the value of Usenet news by sharing our judgements of articles, with our identities pro- tected by pseudonyms. This paper extends the original GroupLens work by reporting on a signi cantly enhanced system and the results of a seven week trial with 250 users and over 20,000 news articles. GroupLens has an open and exible architec- ture that allows easy integration of new news- reader clients and ratings bureaus. We show ratings and prediction pro les for three news- groups, and assess the accuracy of the predictions.
Original language | English (US) |
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State | Published - 1997 |
Event | USENIX 1997 Annual Technical Conference - Anaheim, United States Duration: Jan 6 1997 → Jan 10 1997 |
Conference
Conference | USENIX 1997 Annual Technical Conference |
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Country/Territory | United States |
City | Anaheim |
Period | 1/6/97 → 1/10/97 |
Bibliographical note
Publisher Copyright:© 1997 by The USENIX Association. All Rights Reserved.