title: RACOFI: A Rule-Applying Collaborative Filtering System
creator: Lemire, Daniel
creator: Boley, Harold
subject: Machine Learning
subject: Artificial Intelligence
description: In 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 at http://racofi.elg.ca. .
contributor: Ghorbani, Ali
contributor: Marsh, Stephen
date: 2003
type: Conference Paper
type: PeerReviewed
format: application/pdf
identifier: http://cogprints.org/3166/1/racofi_nrc.pdf
identifier:   Lemire, Daniel and Boley, Harold  (2003) RACOFI: A Rule-Applying Collaborative Filtering System.  [Conference Paper]    (In Press)  
relation: http://cogprints.org/3166/