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Big Data Mining and Analytics  2021, Vol. 4 Issue (1): 47-55    DOI: 10.26599/BDMA.2020.9020015
Special Issue on Intelligent Recommendation System and Big Data Analysis     
Hybrid Recommender System for Tourism Based on Big Data and AI: A Conceptual Framework
Khalid AL Fararni*(),Fouad Nafis(),Badraddine Aghoutane(),Ali Yahyaouy(),Jamal Riffi(),Abdelouahed Sabri()
LISAC Laboratory, Department of Informatics, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez-Atlas 30000, Morocco.
IA Laboratory, Department of Computer Science, Faculty of Sciences, Moulay Ismail University, Meknes 50070, Morocco.
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Abstract  

With the development of the Internet, technology, and means of communication, the production of tourist data has multiplied at all levels (hotels, restaurants, transport, heritage, tourist events, activities, etc.), especially with the development of Online Travel Agency (OTA). However, the list of possibilities offered to tourists by these Web search engines (or even specialized tourist sites) can be overwhelming and relevant results are usually drowned in informational "noise", which prevents, or at least slows down the selection process. To assist tourists in trip planning and help them to find the information they are looking for, many recommender systems have been developed. In this article, we present an overview of the various recommendation approaches used in the field of tourism. From this study, an architecture and a conceptual framework for tourism recommender system are proposed, based on a hybrid recommendation approach. The proposed system goes beyond the recommendation of a list of tourist attractions, tailored to tourist preferences. It can be seen as a trip planner that designs a detailed program, including heterogeneous tourism resources, for a specific visit duration. The ultimate goal is to develop a recommender system based on big data technologies, artificial intelligence, and operational research to promote tourism in Morocco, specifically in the Daraa-Tafilalet region.



Key wordsrecommender systems      user profiling      content-based filtering      collaborative filtering      hybrid recommender system      e-tourism      trip planning     
Received: 31 July 2020      Published: 12 January 2021
Corresponding Authors: Khalid AL Fararni     E-mail: khalid.alfararni@usmba.ac.ma;fouad.nafis@usmba.ac.ma;b.aghoutane@ fpe.umi.ac.ma;ali.yahyaouy@usmba.ac.ma;Jamal.riffi@usmba.ac.ma;abdelouahed.sabri@gmail.com
About author: Khalid AL Fararni is a PhD student in computer science at Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco. He received the master degree in imaging and business intelligence from the same university in 2018. His main research is in the areas of big data, recommender systems, and machine learning.|Fouad Nafis is a PhD student at the Sidi Mohamed Ben Abdellah University. He works as a computer science teacher in the preparatory classes. His research focuses on semantic integration based on several technologies (ontologies, RDF/Owl, SPARQL, etc.) of semantic web, cultural heritage data, open data, linked data, and big data technologies.|Badraddine Aghoutane obtained the PhD degree in computer science from Sidi Mohamed Ben Abdellah University, Morocco in 2011. He is a professor at the Department of Computer Sciences, Faculty of Science, Moulay Imail University, Meknes, Morocco. He joined Moulay Ismail University (UMI) in 2011. He was an assistant professor at the Polydisciplinary Faculty of Errachidia from 2011 to 2019. He is the manager of "software platforms for cataloging, management, and dissemination of the cultural heritage" research project (UMI program-2016) and the member of the CUI-UMI/GIRE project in the framework of VLIR UOS Programs. He is the chairman of the Scientific Committees of SRIE’15, CHAT’19, and MITA’2020 conferences as well. He was also a member of the Organizing and the Scientific Committees of several international symposia and conferences dealing with topics related to computer sciences, technologies, and their applications. His research interest is towards Web semantic, recommender systems, IoT security, and big data.|Ali Yahyaouy is a professor at the Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco. He received the PhD degree from Sidi Mohamed Ben Abdellah University in 2010. His research themes are intelligent homes and transports.|Jamal Riffi obtained the PhD degree in computer science from Sidi Mohamed Ben Abdellah University, Morocco in 2015. He is an assistant professor at the Faculty of Science Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco. His main researches focus on machine learning, medical image analysis, and text mining.|Abdelouahed Sabri is a professor at the Faculty of Science Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco. He received the PhD degree from Sidi Mohamed Ben Abdellah University in 2009. His research areas include image processing and information retrieval.
Cite this article:

Khalid AL Fararni,Fouad Nafis,Badraddine Aghoutane,Ali Yahyaouy,Jamal Riffi,Abdelouahed Sabri. Hybrid Recommender System for Tourism Based on Big Data and AI: A Conceptual Framework. Big Data Mining and Analytics, 2021, 4(1): 47-55.

URL:

http://bigdata.tsinghuajournals.com/10.26599/BDMA.2020.9020015     OR     http://bigdata.tsinghuajournals.com/Y2021/V4/I1/47

Fig. 1 Proposed architecture for tourism recommender system.
Fig. 2 Flowchart of the conceptual framework.
Fig. 3 User profiling, where 1.1 represents that the user profile contains one and only one of each module.
Fig. 4 Web and mobile version of the cultural and natural heritage platform of the Daraa-Tafilalet region.
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