Article: Tourism recommender systems: an overview Journal: International Journal of Cloud Computing (IJCC) 2021 Vol.10 No.5/6 pp.603 - 612 Abstract: The amount of information available on the World Wide Web has increased considerably over the past decade. Information on travel destinations and their associated resources, such as hotels, restaurants, museums or events, etc., is commonly sought by potential tourists and can be useful to plan their trip. However, the list of possibilities offered by web search engines or specialised tourist sites can be overwhelming. Evaluating this long list of options is very complex and time consuming for tourists to choose the best destination suits to their needs. Computer techniques have been developed to facilitate this search as well as the extraction of relevant information. In this article, we will focus on the recommendation systems by providing a detailed and up-to-date review of the most commonly used profiling techniques and recommendation approaches in the field of tourism, with specific emphasis on content-based and collaborative approaches. Inderscience Publishers - linking academia, business and industry through research

Title: Tourism recommender systems: an overview

Authors: Khalid Al Fararni; Badraddine Aghoutane; Ali Yahyaouy; Jamal Riffi; Abdelouahed Sabri

Addresses: LISAC Laboratory, Department of Informatics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, 1796 Fez-Atlas, Fez, Morocco ' IA Laboratory, Department of Computer Science, Faculty of Sciences, Moulay Ismail University, 50070, Meknes, Morocco ' LISAC Laboratory, Department of Informatics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, 1796 Fez-Atlas, Fez, Morocco ' LISAC Laboratory, Department of Informatics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, 1796 Fez-Atlas, Fez, Morocco ' LISAC Laboratory, Department of Informatics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, 1796 Fez-Atlas, Fez, Morocco

Abstract: The amount of information available on the World Wide Web has increased considerably over the past decade. Information on travel destinations and their associated resources, such as hotels, restaurants, museums or events, etc., is commonly sought by potential tourists and can be useful to plan their trip. However, the list of possibilities offered by web search engines or specialised tourist sites can be overwhelming. Evaluating this long list of options is very complex and time consuming for tourists to choose the best destination suits to their needs. Computer techniques have been developed to facilitate this search as well as the extraction of relevant information. In this article, we will focus on the recommendation systems by providing a detailed and up-to-date review of the most commonly used profiling techniques and recommendation approaches in the field of tourism, with specific emphasis on content-based and collaborative approaches.

Keywords: tourism recommender systems; collaborative filtering; content-based filtering; hybrid recommender system; user/item profiling.

DOI: 10.1504/IJCC.2021.120397

International Journal of Cloud Computing, 2021 Vol.10 No.5/6, pp.603 - 612

Received: 05 Jan 2020
Accepted: 28 Mar 2020
Published online: 19 Jan 2022 *

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Title: Tourism recommender systems: an overview

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