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dc.contributor.author
Christensen, Ingrid Alina
dc.contributor.author
Schiaffino, Silvia Noemi
dc.contributor.author
Armentano, Marcelo Gabriel
dc.date.available
2018-09-06T19:44:09Z
dc.date.issued
2016-10
dc.identifier.citation
Christensen, Ingrid Alina; Schiaffino, Silvia Noemi; Armentano, Marcelo Gabriel; Social group recommendation in the tourism domain; Springer; Journal Of Intelligent Information Systems; 47; 2; 10-2016; 209-231
dc.identifier.issn
0925-9902
dc.identifier.uri
http://hdl.handle.net/11336/58605
dc.description.abstract
Recommender Systems learn users’ preferences and tastes in different domains to suggest potentially interesting items to users. Group Recommender Systems generate recommendations that intend to satisfy a group of users as a whole, instead of individual users. In this article, we present a social based approach for recommender systems in the tourism domain, which builds a group profile by analyzing not only users’ preferences, but also the social relationships between members of a group. This aspect is a hot research topic in the recommender systems area. In addition, to generate the individual and group recommendations our approach uses a hybrid technique that combines three well-known filtering techniques: collaborative, content-based and demographic filtering. In this way, the disadvantages of one technique are overcome by the others. Our approach was materialized in a recommender system named Hermes, which suggests tourist attractions to both individuals and groups of users. We have obtained promising results when comparing our approach with classic approaches to generate recommendations to individual users and groups. These results suggest that considering the type of users’ relationship to provide recommendations to groups leads to more accurate recommendations in the tourism domain. These findings can be helpful for recommender systems developers and for researchers in this area.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Recommender Systems
dc.subject
Social Recommender Systems
dc.subject
Tourism
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Social group recommendation in the tourism domain
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-09-05T15:54:08Z
dc.identifier.eissn
1573-7675
dc.journal.volume
47
dc.journal.number
2
dc.journal.pagination
209-231
dc.journal.pais
Alemania
dc.journal.ciudad
Berlín
dc.description.fil
Fil: Christensen, Ingrid Alina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.description.fil
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.description.fil
Fil: Armentano, Marcelo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.journal.title
Journal Of Intelligent Information Systems
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s10844-016-0400-0
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s10844-016-0400-0


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