International Journal of Computational Intelligence Systems (Nov 2024)
Enhancing Fair Tourism Opportunities in Emerging Destinations by Means of Multi-criteria Recommender Systems: The Case of Restaurants in Riohacha, Colombia
Abstract
Abstract This study addresses the problem of recommending restaurants in emerging tourist destinations, taking into account factors vital in these locations, such as location, safety, price and services. The novel recommendation model is based on the well-known logical scoring of preferences (LSP) methodology. The system considers individual preferences across a hierarchy of criteria. The user can customize the recommender by providing suitability scores and aggregation operators for each criterion. The first contribution is the identification of relevant criteria for the selection of restaurants in emerging destinations and the definition of a new scoring system to manage user preferences regarding types of food. The second contribution of this study is the selection of appropriate conjunctive/disjunctive aggregation operators. The recommender system has been tested in a use case in Riohacha (Colombia), obtaining promising results in a wide range of user profiles.
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