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Fuzzy ontology as a basis for recommendation Systems for Traveler’s preference

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Abstract

As an increasingly larger number of users partake in Facebook, the images shared and posted by user in Facebook provide a richer background to build a more accurate recommendation system. In this paper, we propose an Intelligent Recommendation System for Travelers’ Preferences (IRSTP) based on the conceptualization of the travel user’s destination based on their activities of sharing visual data and locations through social network. In this system, we performed a Deep Neural Network Architecture transferred on Places356 database to extract important concepts found in the shared visual images. Then, we carried out an inference system based on crisp (DOVUIS) and fuzzy ontology (DFOVUIS) to take into account some ambiguity in Decision making. Both proposed ontologies are tested and evaluated on collected Sudanese Database. The User interest architecture based on Convolutional Neural Network is used for tuning search in the IRSTP recommendation system. The Fuzzy ontology performs well than the crisp inference system in order to personalize the recommendation based on the profile outputted from this ontology. We achieve an accuracy of 94.22\% on the Sudanese database to classify the topic of user interest among 9 classes Food (98.7%), Nature (98.9%), History (80.4%), DIY and Craft (98.0%), Celebrities (87.3%), Architectures (98.6%), Events (95.4%), Holydays (93.9%) and Art (87.0%). These topics are considered from the Facebook generic topics.

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Acknowledgments

This research was supported by Research Groups in Intelligent Machines (ReGIM-Lab). We thank Wael Ouarda, a Professor-Researcher in Computer Science at the University of Sfax and quality manager at the ReGIM-Lab at the University of Sfax for comments that greatly improved the manuscript and we thank Adel M. Alimi professor in Electrical and Computer Engineering at the University of Sfax for assistance with application of intelligent methods (neural networks, fuzzy logic) to pattern recognition.

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Authors and Affiliations

  1. Sudan University of Science and Technology, College of Post-graduate Studies, Khartoum, Sudan

    Fatima Mohamed Yassin

  2. Centre de Recherche en Numérique de Sfax (CRNS), Sfax, Tunisia

    Fatima Mohamed Yassin, Wael Ouarda & Adel M. Alimi

  3. Department of Electrical and Electronic Engineering Science, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

    Adel M. Alimi

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  1. Fatima Mohamed Yassin
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Correspondence to Fatima Mohamed Yassin.

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Yassin, F.M., Ouarda, W. & Alimi, A.M. Fuzzy ontology as a basis for recommendation Systems for Traveler’s preference. Multimed Tools Appl 81, 6599–6631 (2022). https://doi.org/10.1007/s11042-021-11780-5

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  • DOI: https://doi.org/10.1007/s11042-021-11780-5

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