Entertainment recommender systems for group of users

Autores
Christensen, Ingrid Alina; Schiaffino, Silvia Noemi
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Recommender systems are used to recommend potentially interesting items to users in different domains. Nowadays, there is a wide range of domains in which there is a need to offer recommendations to group of users instead of individual users. As a consequence, there is also a need to address the preferences of individual members of a group of users so as to provide suggestions for groups as a whole. Group recommender systems present a whole set of new challenges within the field of recommender systems. In this article, we present two expert recommender systems that suggest entertainment to groups of users. These systems, jMusicGroupRecommender and jMoviesGroupRecommender, suggest music and movies and utilize different methods for the generation of group recommendations: merging recommendations made for individuals, aggregation of individuals' ratings, and construction of group preference models. We also describe the results obtained when comparing different group recommendation techniques in both domains.
Fil: Christensen, Ingrid Alina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Schiaffino, Silvia Noemi. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
GROUP MODEL
GROUP RECOMMENDER SYSTEM
PREFERENCE AGGREGATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/96546
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Entertainment recommender systems for group of usersChristensen, Ingrid AlinaSchiaffino, Silvia NoemiGROUP MODELGROUP RECOMMENDER SYSTEMPREFERENCE AGGREGATIONhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Recommender systems are used to recommend potentially interesting items to users in different domains. Nowadays, there is a wide range of domains in which there is a need to offer recommendations to group of users instead of individual users. As a consequence, there is also a need to address the preferences of individual members of a group of users so as to provide suggestions for groups as a whole. Group recommender systems present a whole set of new challenges within the field of recommender systems. In this article, we present two expert recommender systems that suggest entertainment to groups of users. These systems, jMusicGroupRecommender and jMoviesGroupRecommender, suggest music and movies and utilize different methods for the generation of group recommendations: merging recommendations made for individuals, aggregation of individuals' ratings, and construction of group preference models. We also describe the results obtained when comparing different group recommendation techniques in both domains.Fil: Christensen, Ingrid Alina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Schiaffino, Silvia Noemi. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaPergamon-Elsevier Science Ltd2011-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/96546Christensen, Ingrid Alina; Schiaffino, Silvia Noemi; Entertainment recommender systems for group of users; Pergamon-Elsevier Science Ltd; Expert Systems with Applications; 38; 11; 10-2011; 14127-141350957-4174CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.eswa.2011.04.221info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0957417411007482info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:14:12Zoai:ri.conicet.gov.ar:11336/96546instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:14:13.194CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Entertainment recommender systems for group of users
title Entertainment recommender systems for group of users
spellingShingle Entertainment recommender systems for group of users
Christensen, Ingrid Alina
GROUP MODEL
GROUP RECOMMENDER SYSTEM
PREFERENCE AGGREGATION
title_short Entertainment recommender systems for group of users
title_full Entertainment recommender systems for group of users
title_fullStr Entertainment recommender systems for group of users
title_full_unstemmed Entertainment recommender systems for group of users
title_sort Entertainment recommender systems for group of users
dc.creator.none.fl_str_mv Christensen, Ingrid Alina
Schiaffino, Silvia Noemi
author Christensen, Ingrid Alina
author_facet Christensen, Ingrid Alina
Schiaffino, Silvia Noemi
author_role author
author2 Schiaffino, Silvia Noemi
author2_role author
dc.subject.none.fl_str_mv GROUP MODEL
GROUP RECOMMENDER SYSTEM
PREFERENCE AGGREGATION
topic GROUP MODEL
GROUP RECOMMENDER SYSTEM
PREFERENCE AGGREGATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Recommender systems are used to recommend potentially interesting items to users in different domains. Nowadays, there is a wide range of domains in which there is a need to offer recommendations to group of users instead of individual users. As a consequence, there is also a need to address the preferences of individual members of a group of users so as to provide suggestions for groups as a whole. Group recommender systems present a whole set of new challenges within the field of recommender systems. In this article, we present two expert recommender systems that suggest entertainment to groups of users. These systems, jMusicGroupRecommender and jMoviesGroupRecommender, suggest music and movies and utilize different methods for the generation of group recommendations: merging recommendations made for individuals, aggregation of individuals' ratings, and construction of group preference models. We also describe the results obtained when comparing different group recommendation techniques in both domains.
Fil: Christensen, Ingrid Alina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Schiaffino, Silvia Noemi. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Recommender systems are used to recommend potentially interesting items to users in different domains. Nowadays, there is a wide range of domains in which there is a need to offer recommendations to group of users instead of individual users. As a consequence, there is also a need to address the preferences of individual members of a group of users so as to provide suggestions for groups as a whole. Group recommender systems present a whole set of new challenges within the field of recommender systems. In this article, we present two expert recommender systems that suggest entertainment to groups of users. These systems, jMusicGroupRecommender and jMoviesGroupRecommender, suggest music and movies and utilize different methods for the generation of group recommendations: merging recommendations made for individuals, aggregation of individuals' ratings, and construction of group preference models. We also describe the results obtained when comparing different group recommendation techniques in both domains.
publishDate 2011
dc.date.none.fl_str_mv 2011-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/96546
Christensen, Ingrid Alina; Schiaffino, Silvia Noemi; Entertainment recommender systems for group of users; Pergamon-Elsevier Science Ltd; Expert Systems with Applications; 38; 11; 10-2011; 14127-14135
0957-4174
CONICET Digital
CONICET
url http://hdl.handle.net/11336/96546
identifier_str_mv Christensen, Ingrid Alina; Schiaffino, Silvia Noemi; Entertainment recommender systems for group of users; Pergamon-Elsevier Science Ltd; Expert Systems with Applications; 38; 11; 10-2011; 14127-14135
0957-4174
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.eswa.2011.04.221
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0957417411007482
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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