García García, I.; Pajares Ferrando, S.; Sebastiá Tarín, L.; Onaindia De La Rivaherrera, E. (2012). Preference elicitation techniques for group recommender systems. Information Sciences. 189:155-175. doi:10.1016/j.ins.2011.11.037
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/35736
Title:
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Preference elicitation techniques for group recommender systems
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Author:
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García García, Inmaculada
Pajares Ferrando, Sergio
Sebastiá Tarín, Laura
Onaindia de la Rivaherrera, Eva
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UPV Unit:
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Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
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Issued date:
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Abstract:
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A key issue in group recommendation is how to combine the individual preferences of different users that form a group and elicit a profile that accurately reflects the tastes of all members in the group. Most Group Recommender ...[+]
A key issue in group recommendation is how to combine the individual preferences of different users that form a group and elicit a profile that accurately reflects the tastes of all members in the group. Most Group Recommender Systems (GRSs) make use of some sort of method for aggregating the preference models of individual users to elicit a recommendation that is satisfactory for the whole group. In general, most GRSs offer good results, but each of them have only been tested in one application domain. This paper describes a domain-independent GRS that has been used in two different application domains. In order to create the group preference model, we select two techniques that are widely used in other GRSs and we compare them with two novel techniques. Our aim is to come up with a model that weighs the preferences of all the individuals to the same extent in such a way that no member in the group is particularly satisfied or dissatisfied with the final recommendations. © 2011 Elsevier Inc. All rights reserved.
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Subjects:
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Group profile
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Group recommender systems
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Preference elicitation
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Application domains
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Individual preference
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Novel techniques
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Preference elicitation techniques
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Preference models
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Artificial intelligence
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Software engineering
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Recommender systems
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Copyrigths:
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Reserva de todos los derechos
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Source:
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Information Sciences. (issn:
0020-0255
)
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DOI:
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10.1016/j.ins.2011.11.037
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Publisher:
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Elsevier
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Publisher version:
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http://dx.doi.org/10.1016/j.ins.2011.11.037
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Project ID:
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Consolider Ingenio [CSD2007-00022]
Spanish Government [MICINN TIN2008-6701-C03-01]
Valencian Government [Prometeo 2008/051]
FPU [AP2009-1896]
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Thanks:
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Partial support provided by Consolider Ingenio 2010 CSD2007-00022, Spanish Government Project MICINN TIN2008-6701-C03-01 and Valencian Government Project Prometeo 2008/051. FPU grant reference AP2009-1896 awarded to Sergio ...[+]
Partial support provided by Consolider Ingenio 2010 CSD2007-00022, Spanish Government Project MICINN TIN2008-6701-C03-01 and Valencian Government Project Prometeo 2008/051. FPU grant reference AP2009-1896 awarded to Sergio Pajares-Ferrando.
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Type:
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Artículo
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