Combining collaborative filtering with personal agents for better recommendations

Nathaniel Good, J. Ben Schafer, Joseph A. Konstan, Al Borchers, Badrul Sarwar, Jon Herlocker, John Riedl

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

503 Scopus citations

Abstract

Collaborative filtering (CF) shows potential to combine personal information filtering (IF) agents and the opinions of a community of users to produce better recommendations than either agents or users can produce alone. Using CF to create a personal combination of a set of agents produces better results than either individual agents or other combination mechanisms. Overall, users can avoid having to select among agents; they can use them all and let the CF framework select the best ones for them.

Original languageEnglish (US)
Title of host publicationProceedings of the National Conference on Artificial Intelligence
PublisherAAAI
Pages439-446
Number of pages8
ISBN (Print)0262511061
StatePublished - Jan 1 1999
EventProceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99), 11th Innovative Applications of Artificial Intelligence Conference (IAAI-99) - Orlando, FL, USA
Duration: Jul 18 1999Jul 22 1999

Publication series

NameProceedings of the National Conference on Artificial Intelligence

Other

OtherProceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99), 11th Innovative Applications of Artificial Intelligence Conference (IAAI-99)
CityOrlando, FL, USA
Period7/18/997/22/99

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