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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/123735
Ver los metadatos del registro completo
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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:UNLP2025-09-03T11:01:44Zoai: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:13292025-09-03 11:01:44.854SEDICI (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 http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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http://sedici.unlp.edu.ar/handle/10915/123735 |
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http://sedici.unlp.edu.ar/handle/10915/123735 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 116-127 |
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