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https://hdl.handle.net/1822/69226
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Campo DC | Valor | Idioma |
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dc.contributor.author | Alves, Patrícia | por |
dc.contributor.author | Saraiva, Pedro | por |
dc.contributor.author | Carneiro, João | por |
dc.contributor.author | Campos, Pedro | por |
dc.contributor.author | Martins, Helena | por |
dc.contributor.author | Novais, Paulo | por |
dc.contributor.author | Marreiros, Goreti | por |
dc.date.accessioned | 2021-01-14T11:51:31Z | - |
dc.date.available | 2021-01-14T11:51:31Z | - |
dc.date.issued | 2020-07-07 | - |
dc.identifier.citation | Alves, P., Saraiva, P., Carneiro, J., Campos, P., Martins, H., Novais, P., & Marreiros, G. (2020, July). Modeling Tourists' Personality in Recommender Systems: How Does Personality Influence Preferences for Tourist Attractions?. In Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (pp. 4-13). | por |
dc.identifier.isbn | 9781450368612 | por |
dc.identifier.uri | https://hdl.handle.net/1822/69226 | - |
dc.description.abstract | Personalization 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. | por |
dc.description.sponsorship | GrouPlanner Project under the European Regional Development Fund POCI-01-0145-FEDER29178 and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UIDB/00319/2020 and UIDB/00760/2020 | por |
dc.language.iso | eng | por |
dc.publisher | Association for Computing Machinery (ACM) | por |
dc.rights | openAccess | por |
dc.subject | Affective computing | por |
dc.subject | Leisure tourism | por |
dc.subject | Personality | por |
dc.subject | Recommender systems | por |
dc.subject | Tourist preferences | por |
dc.title | Modeling tourists' personality in recommender systems: how does personality influence preferences for tourist attractions? | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://dl.acm.org/doi/abs/10.1145/3340631.3394843 | por |
oaire.citationStartPage | 4 | por |
oaire.citationEndPage | 13 | por |
dc.date.updated | 2020-12-30T20:07:31Z | - |
dc.identifier.doi | 10.1145/3340631.3394843 | por |
dc.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | por |
dc.subject.fos | Ciências Sociais::Outras Ciências Sociais | por |
dc.subject.wos | Science & Technology | por |
sdum.export.identifier | 7677 | - |
sdum.conferencePublication | UMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization | por |
sdum.bookTitle | UMAP'20: PROCEEDINGS OF THE 28TH ACM CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION | por |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Modeling Tourists’ Personality in Recommender Systems.pdf | 728,4 kB | Adobe PDF | Ver/Abrir |