IDENTIFYING SIMILAR USERS BY THEIR SCIENTIFIC PUBLICATIONS TO REDUCE COLD START IN RECOMMENDER SYSTEMS

Stanley Loh, Fabiana Lorenzi, Roger Granada, Daniel Lichtnow, Leandro Krug Wives, José Palazzo Moreira de Oliveira

Abstract

This paper presents investigations on representing user’s profiles with information extracted from their scientific publications. The work assumes that scientific papers written by users can be used to represent user’s interest or expertise and that these representations can be used to find similar users. The goal is to support similarity evaluations between users in a model-based collaborative recommender. Representing users by their publications can help minimizing the new user problem. The idea is to avoid the necessity of asking users to evaluate a set of items or give some information about their preferences, for example. In scientific communities, particularly on digital libraries and systems focused on the retrieval of scientific papers, this is an interesting feature. We have conducted some experiments to compare different techniques to represent the papers (title, keywords, abstract and complete text) and two kinds of text indexes: terms and concepts. Furthermore, two distinct similarity functions (Jaccard and a Fuzzy function) were applied on these representations and then compared with the goal of finding similar users.

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Paper Citation


in Harvard Style

Loh S., Lorenzi F., Granada R., Lichtnow D., Krug Wives L. and Palazzo Moreira de Oliveira J. (2009). IDENTIFYING SIMILAR USERS BY THEIR SCIENTIFIC PUBLICATIONS TO REDUCE COLD START IN RECOMMENDER SYSTEMS . In Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8111-81-4, pages 589-596. DOI: 10.5220/0001823405890596


in Bibtex Style

@conference{webist09,
author={Stanley Loh and Fabiana Lorenzi and Roger Granada and Daniel Lichtnow and Leandro Krug Wives and José Palazzo Moreira de Oliveira},
title={IDENTIFYING SIMILAR USERS BY THEIR SCIENTIFIC PUBLICATIONS TO REDUCE COLD START IN RECOMMENDER SYSTEMS},
booktitle={Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2009},
pages={589-596},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001823405890596},
isbn={978-989-8111-81-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - IDENTIFYING SIMILAR USERS BY THEIR SCIENTIFIC PUBLICATIONS TO REDUCE COLD START IN RECOMMENDER SYSTEMS
SN - 978-989-8111-81-4
AU - Loh S.
AU - Lorenzi F.
AU - Granada R.
AU - Lichtnow D.
AU - Krug Wives L.
AU - Palazzo Moreira de Oliveira J.
PY - 2009
SP - 589
EP - 596
DO - 10.5220/0001823405890596