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From "I like" to "I prefer" in Collaborative Filtering

Armelle Brun 1 Ahmad Hamad 1 Olivier Buffet 2 Anne Boyer 1
1 KIWI - Knowledge Information and Web Intelligence
LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Collaborative filtering exploits user preferences, generally ratings, to provide them with recommendations. However, the ratings may not be completely trustworthy: the rating scale is usually reduced and the rating values may be influenced by many factors. This paper is a first attempt at studying the expression of preferences under the form of preference relations where users are asked to compare pairs of resources. First experiments show that this new approach compares with, and sometimes improves, the classical one.
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Submitted on : Thursday, November 11, 2010 - 10:51:57 PM
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Armelle Brun, Ahmad Hamad, Olivier Buffet, Anne Boyer. From "I like" to "I prefer" in Collaborative Filtering. International Conference on Tools with Artificial Intelligence - ICTAI 2010, Oct 2010, Arras, France. ⟨inria-00535566⟩

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