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Social trust based semantic tourism recommender system: a case of medical tourism in Tunisia / Mohamed Frikha, Mohamed Ben Ahmed Mhiri, Faiez Gargouri

Main Author Frikha, Mohamed Coauthor Mhiri, Mohamed Ben Ahmed
Gargouri, Faiez Abstract Based on the assumption that users generally have a tendency to use items recommended by friends rather than strangers and that trust among friends positively correlates with user preference, we decided to refer to research conducted on the emerging field of trust-based recommender system. We propose to integrate the temporal factor in measuring trust between social network friends. A Trusted Friend’s calculation method is developed for determining social trusted friends in Facebook. We have, accordingly, demonstrated the importance of the interactions’ time between users. Afterwards, we have used this method in a semantic tourism recommender system as a smart e-tourism tool able to recommend items based on the users’ preferences and their trusted friends’ preferences. We have also applied our tourism recommender system for the case of medical tourism in Tunisia to help users interested in travelling to Tunisia for medical purposes. Finally, we have implemented the system and collected feedback from real users to evaluate the quality of recommendation and prove its importance in improving the medical tourism domain. Analytic European Journal of Tourism Research, vol. 17 (2017), pp. 59-82 Topical name Turismo
Turismo de saúde e bem-estar
Turismo médico
Redes sociais
Turistas - Preferências Geographical name Tunísia Form or physical characteristic Artigos em periódicos
Publicações em acesso aberto CDU 338.48(045) Online Resources Leia aqui este artigo
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Holdings
Item type Current location Call number Vol info Status Date due Barcode Item holds
Article Biblioteca Universidade Europeia (QBN)
Periódicos Biblioteca 		BIPAM-LX PER-14 vol. 17 (2017), pp. 59-82 Presencial/Restrito 3845-9733j
Total holds: 0

Based on the assumption that users generally have a tendency to use items recommended by friends rather than strangers and that trust among friends positively correlates with user preference, we decided to refer to research conducted on the emerging field of trust-based recommender system. We propose to integrate the temporal factor in measuring trust between social network friends. A Trusted Friend’s calculation method is developed for determining social trusted friends in Facebook. We have, accordingly, demonstrated the importance of the interactions’ time between users. Afterwards, we have used this method in a semantic tourism recommender system as a smart e-tourism tool able to recommend items based on the users’ preferences and their trusted friends’ preferences. We have also applied our tourism recommender system for the case of medical tourism in Tunisia to help users interested in travelling to Tunisia for medical purposes. Finally, we have implemented the system and collected feedback from real users to evaluate the quality of recommendation and prove its importance in improving the medical tourism domain.

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