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Modeling Tourists' Personality in Recommender Systems

dc.contributor.authorAlves, Patrícia
dc.contributor.authorSaraiva, Pedro
dc.contributor.authorCarneiro, João
dc.contributor.authorCampos, Pedro
dc.contributor.authorMartins, Helena
dc.contributor.authorNovais, Paulo
dc.contributor.authorMarreiros, Goreti
dc.date.accessioned2022-01-11T16:23:27Z
dc.date.available2022-01-11T16:23:27Z
dc.date.issued2020
dc.description.abstractPersonalization is increasingly being perceived as an important factor for the effectiveness of Recommender Systems (RS). This is especially true in the tourism domain, where travelling comprises emotionally charged experiences, and therefore, the more about the tourist is known, better recommendations can be made. The inclusion of psychological aspects to generate recommendations, such as personality, is a growing trend in RS and they are being studied to provide more personalized approaches. However, although many studies on the psychology of tourism exist, studies on the prediction of tourist preferences based on their personality are limited. Therefore, we undertook a large-scale study in order to determine how the Big Five personality dimensions influence tourists' preferences for tourist attractions, gathering data from an online questionnaire, sent to Portuguese individuals from the academic sector and their respective relatives/friends (n=508). Using Exploratory and Confirmatory Factor Analysis, we extracted 11 main categories of tourist attractions and analyzed which personality dimensions were predictors (or not) of preferences for those tourist attractions. As a result, we propose the first model that relates the five personality dimensions with preferences for tourist attractions, which intends to offer a base for researchers of RS for tourism to automatically model tourist preferences based on their personality.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1145/3340631.3394843pt_PT
dc.identifier.isbn978-1-4503-6861-2
dc.identifier.urihttp://hdl.handle.net/10400.22/19402
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherACMpt_PT
dc.relation.publisherversionhttps://dl.acm.org/doi/10.1145/3340631.3394843pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectRecommender Systemspt_PT
dc.subjectPersonalitypt_PT
dc.subjectTourist Preferencespt_PT
dc.subjectAffective Computingpt_PT
dc.subjectLeisure Tourismpt_PT
dc.titleModeling Tourists' Personality in Recommender Systemspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceGenoa, Italypt_PT
oaire.citation.endPage13pt_PT
oaire.citation.startPage4pt_PT
oaire.citation.titleUMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalizationpt_PT
person.familyNameAlves
person.familyNameCarneiro
person.givenNamePatrícia
person.givenNameJoão
person.identifier.ciencia-idAE10-74A4-9DC6
person.identifier.orcid0000-0003-3997-311X
person.identifier.orcid0000-0003-1430-5465
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationa19bccef-3188-4ef2-bacf-b0b2400b3cf0
relation.isAuthorOfPublicatione6c3294b-e8d7-45ac-9303-f763b9257745
relation.isAuthorOfPublication.latestForDiscoverya19bccef-3188-4ef2-bacf-b0b2400b3cf0

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