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Authors: Jean-Francois Pessiot ; Tuong-Vinh Truong ; Nicolas Usunier ; Massih-Reza Amini and Patrick Gallinari

Affiliation: University of Paris VI, France

Keyword(s): Collaborative Filtering, Recommender Systems, Machine Learning, Ranking.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Industrial Applications of Artificial Intelligence ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Up to now, most contributions to collaborative filtering rely on rating prediction to generate the recommendations. We, instead, try to correctly rank the items according to the users’ tastes. First, we define a ranking error function which takes available pairwise preferences between items into account. Then we design an effective algorithm that optimizes this error. Finally we illustrate the proposal on a standard collaborative filtering dataset. We adapted the evaluation protocol proposed by (Marlin, 2004) for rating prediction based systems to our case, where pairwise preferences are predicted instead. The preliminary results are between those of two reference rating prediction based methods. We suggest different directions to further explore our ranking based approach for collaborative filtering.

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Paper citation in several formats:
Pessiot, J.; Truong, T.; Usunier, N.; Amini, M. and Gallinari, P. (2007). LEARNING TO RANK FOR COLLABORATIVE FILTERING. In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-89-4; ISSN 2184-4992, SciTePress, pages 145-151. DOI: 10.5220/0002396301450151

@conference{iceis07,
author={Jean{-}Francois Pessiot. and Tuong{-}Vinh Truong. and Nicolas Usunier. and Massih{-}Reza Amini. and Patrick Gallinari.},
title={LEARNING TO RANK FOR COLLABORATIVE FILTERING},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2007},
pages={145-151},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002396301450151},
isbn={978-972-8865-89-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - LEARNING TO RANK FOR COLLABORATIVE FILTERING
SN - 978-972-8865-89-4
IS - 2184-4992
AU - Pessiot, J.
AU - Truong, T.
AU - Usunier, N.
AU - Amini, M.
AU - Gallinari, P.
PY - 2007
SP - 145
EP - 151
DO - 10.5220/0002396301450151
PB - SciTePress