An Analysis of the Impact of Estimating Ratings on Group Recommender Systems

Autores
Christensen, Ingrid; Schiafino, Silvia
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Nowadays, there is a wide range of domains in which there is a need to generate recommendations to groups of users instead of individuals. Several techniques for aggregating individual models or ratings have been developed; a disadvantage of these techniques is that they require a large amount of computations to estimate unknown ratings. In this article, we present an analysis of the impact of estimating ratings when an aggregation technique is used. For that purpose, we describe a hybrid approach to generate group recommendations based on group modeling. We also present the results obtained when evaluating the approach and two well-known aggregation techniques in the movie domain, and the variations of those results when the estimation process is not included.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Group Recommendation
Group Profiling
Aggregate Ratings
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/123735
Acceder
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network_name_str SEDICI (UNLP)
spelling An Analysis of the Impact of Estimating Ratings on Group Recommender SystemsChristensen, IngridSchiafino, SilviaCiencias InformáticasGroup RecommendationGroup ProfilingAggregate RatingsNowadays, there is a wide range of domains in which there is a need to generate recommendations to groups of users instead of individuals. Several techniques for aggregating individual models or ratings have been developed; a disadvantage of these techniques is that they require a large amount of computations to estimate unknown ratings. In this article, we present an analysis of the impact of estimating ratings when an aggregation technique is used. For that purpose, we describe a hybrid approach to generate group recommendations based on group modeling. We also present the results obtained when evaluating the approach and two well-known aggregation techniques in the movie domain, and the variations of those results when the estimation process is not included.Sociedad Argentina de Informática e Investigación Operativa2012-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf116-127http://sedici.unlp.edu.ar/handle/10915/123735enginfo:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/11_ASAI_2012.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2784info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:29:39Zoai:sedici.unlp.edu.ar:10915/123735Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:29:39.589SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
title An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
spellingShingle An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
Christensen, Ingrid
Ciencias Informáticas
Group Recommendation
Group Profiling
Aggregate Ratings
title_short An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
title_full An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
title_fullStr An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
title_full_unstemmed An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
title_sort An Analysis of the Impact of Estimating Ratings on Group Recommender Systems
dc.creator.none.fl_str_mv Christensen, Ingrid
Schiafino, Silvia
author Christensen, Ingrid
author_facet Christensen, Ingrid
Schiafino, Silvia
author_role author
author2 Schiafino, Silvia
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Group Recommendation
Group Profiling
Aggregate Ratings
topic Ciencias Informáticas
Group Recommendation
Group Profiling
Aggregate Ratings
dc.description.none.fl_txt_mv Nowadays, there is a wide range of domains in which there is a need to generate recommendations to groups of users instead of individuals. Several techniques for aggregating individual models or ratings have been developed; a disadvantage of these techniques is that they require a large amount of computations to estimate unknown ratings. In this article, we present an analysis of the impact of estimating ratings when an aggregation technique is used. For that purpose, we describe a hybrid approach to generate group recommendations based on group modeling. We also present the results obtained when evaluating the approach and two well-known aggregation techniques in the movie domain, and the variations of those results when the estimation process is not included.
Sociedad Argentina de Informática e Investigación Operativa
description Nowadays, there is a wide range of domains in which there is a need to generate recommendations to groups of users instead of individuals. Several techniques for aggregating individual models or ratings have been developed; a disadvantage of these techniques is that they require a large amount of computations to estimate unknown ratings. In this article, we present an analysis of the impact of estimating ratings when an aggregation technique is used. For that purpose, we describe a hybrid approach to generate group recommendations based on group modeling. We also present the results obtained when evaluating the approach and two well-known aggregation techniques in the movie domain, and the variations of those results when the estimation process is not included.
publishDate 2012
dc.date.none.fl_str_mv 2012-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/123735
url http://sedici.unlp.edu.ar/handle/10915/123735
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1850-2784
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
116-127
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reponame_str SEDICI (UNLP)
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instname_str Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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