An Innovative Recommender System for Health Tourism

Antiopi Panteli (), Aristotelis Kompothrekas, Constantinos Halkiopoulos and Basilis Boutsinas
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Antiopi Panteli: MISBILAB, University of Patras
Aristotelis Kompothrekas: MISBILAB, University of Patras
Constantinos Halkiopoulos: MISBILAB, University of Patras
Basilis Boutsinas: MISBILAB, University of Patras

A chapter in Culture and Tourism in a Smart, Globalized, and Sustainable World, 2021, pp 649-658 from Springer

Abstract: Abstract The recommender systems process data for extracting information relevant to the user profile. In this study, we present an innovative recommender system aiming at matching health tourist preferences to health/tourism providers. It focuses on providing complete health tourism products, by matching the user profile to characteristics of both health and tourism service providers, in order that users receive the treatment they choose in the right location, the right period and at the right cost. The proposed recommender system is implemented by applying a facility location problem which employs a parameter that controls the diversity of the recommendation list and thus the variety of the proposed results. It incorporates a database of cases, i.e., medical, wellness and tourism service providers. A case is described by a set of attributes such as medical service category, spa category, wellness category, cost, infrastructure, accreditations, communication languages and so on. Users that have already acquired a health tourism package provide ratings for certain categories of attributes. A new user expresses her preferences in the form of a query, and then, the system tries to match this query to the cases that exist in the database. At first, the best possible cases are extracted, by applying a sorting procedure based on comparisons to the ideal one, i.e., that containing the best ratings for each attribute of the database. Then, the facility location method is applied to provide the final recommended cases to the user that are both similar to the provided query and diverse to each other.

Keywords: Recommender system; Health tourism; Hotel industry; Digital marketing (search for similar items in EconPapers)
JEL-codes: C38 C44 M31 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-72469-6_42

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DOI: 10.1007/978-3-030-72469-6_42

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