RACOFI: A Rule-Applying Collaborative Filtering System

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TypeArticle
ConferenceInternational Workshop on Collaboration Agents: Autonomous Agents for Collaborative Environments (COLA'03), October 13, 2003., Halifax, Nova Scotia, Canada
AbstractIn this paper we give an overview of the RACOFI (Rule-Applying Collaborative Filtering) multidimensional rating system and its related technologies. This will be exemplified with RACOFI Music, an implemented collaboration agent that assists on-line users in the rating and recommendation of audio (Learning) Objects. It lets users rate contemporary Canadian music in the five dimensions of impression, lyrics, music, originality, and production. The collaborative filtering algorithms STI Pearson, STIN2, and the Per Item Average algorithms are then employed together with RuleML-based rules to recommend music objects that best match user queries. RACOFI has been on-line since August 2003.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number46507
NPARC number8913490
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Record identifier30df9c1e-9ab8-4c92-9aa3-9e5afe8c8564
Record created2009-04-22
Record modified2016-05-09
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