Abstract

Tourism is an economic and a wealth-creating pillar that involves several volatile actors that are rich in dynamic, complex and heterogeneous information (Benckendorff et al., 2019). Therein, the continuous increase in the volume of information available on tourism offerings on the web has made user decision making a crucial task. As a result, the use of personalized and intelligent recommendation systems is essential for the satisfaction of tourism consumers (Grün et al., 2017). The objective of this article is to reveal the impact of the deployment of semantic techniques on the quality and accuracy of search results for tourism information, in the case of tourism in Morocco. This will be done through ontologies, which are a key component in the semantic web (Buhalis, 2020). To this end, we first presented the implementation of the semantic web and the use of ontologies in it. Then, we described the basic background of ontologies. Finally, we discussed the existing ontologies in the tourism domain in Morocco. The findings show that, the assumption of ontological conceptualization during the creation of digital content by tourism establishments, as a context-aware knowledge base, ensures the implementation of a semantic correspondence between users' preferences and the characteristics of tourism offers published, thus improving the quality and accuracy of the recommendations according to the user's context (Abbasi-Moud et al., 2022). Nevertheless, the evolution of tourism ontologies following changes in this sector is of major complexity. For this reason, the invention of an automatic approach, based on artificial intelligence techniques, NLP, Machine Learning or Deep Learning, can contribute to an evolutionary, reliable and easier maintenance of tourism ontologies, in the Moroccan context.

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