Abstract
Due to the widespread diffusion of information technologies and the number of social network users who are increasing day after day, today there is an explosion of data on the web, which requires a filtering mechanism to customize the data to be displayed to the users according to their needs. For this reason, the recommendation systems have been designed to facilitate and personalize data access, according to the needs of each user. But each system can recommend services linking to a specific area, which makes the system of recommendations point and more efficient, where we find systems for the field of e-commerce, tourism, etc. In this paper, our work focuses on designing an intelligent recommendation system for the tourism field, which is used to analyze images stored in mobile devices of users in order to identify the fields of interest of these users (keywords). Then, we base on these latter to recommend the tourist services and places suitable to each user according to their preferences.
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Daoui, A., Gherabi, N., Marzouk, A. (2021). Smart Tourism Recommender System Using Semantic Matching. In: Gherabi, N., Kacprzyk, J. (eds) Intelligent Systems in Big Data, Semantic Web and Machine Learning. Advances in Intelligent Systems and Computing, vol 1344. Springer, Cham. https://doi.org/10.1007/978-3-030-72588-4_2
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DOI: https://doi.org/10.1007/978-3-030-72588-4_2
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