Artículo
Towards an argument-based music recommender system
Briguez, Cristian Emanuel
; Budan, Maximiliano Celmo David
; Deagustini, Cristhian Ariel David
; Maguitman, Ana Gabriela
; Capobianco, Marcela
; Simari, Guillermo Ricardo
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Fecha de publicación:
09/2012
Editorial:
IOS Press
Revista:
Frontiers in Artificial Intelligence and Applications
ISSN:
0922-6389
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The significance of recommender systems has steadily grown in recent years as they help users to access relevant items from the vast universe of possibilities available these days. However, most of the research in recommenders is based purely on quantitative aspects, i.e., measures of similarity between items or users. In this paper we introduce a novel hybrid approach to refine recommendations achieved by quantitative methods with a qualitative approach based on argumentation, where suggestions are given after considering several arguments in favor or against the recommendations. In order to accomplish this, we use Defeasible Logic Programming (DeLP) as the underlying formalism for obtaining recommendations. This approach has a number of advantages over other existing recommendation techniques.In particular, recommendations can be refined at any time by adding new polished rules, and explanations may be provided supporting each recommendation in a way that can be easily understood by the user, by means of the computed arguments.
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Articulos(CCT - BAHIA BLANCA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - BAHIA BLANCA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - BAHIA BLANCA
Citación
Briguez, Cristian Emanuel; Budan, Maximiliano Celmo David; Deagustini, Cristhian Ariel David; Maguitman, Ana Gabriela; Capobianco, Marcela; et al.; Towards an argument-based music recommender system; IOS Press; Frontiers in Artificial Intelligence and Applications; 245; 1; 9-2012; 83-90
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