DOI: 10.17587/prin.15.425-433

Tourism Application Development with a Recommendation System based on Fuzzy Logic

I. Y. Kotsyuba, Ph.D. (Technical Science), Associate Professor, igor.kotciuba@gmail.com, I. S. Blinov, Master's Student, isblinov0@outlook.com, ITMO University, Saint Petersburg, 197101, Russian Federation

Corresponding author: Ivan S. Blinov, Masters Student, ITMO University, Saint Petersburg, 197101, Russian Federation E-mail: isblinov0@outlook.com

The article addresses issues related to the breadth and multifaceted aspects of the tourism industry. It discusses the practical benefits of using recommendation systems based on mobile devices. Mobile applications with recom­mendation systems play an important role in the tourism planning process, offering users personalized suggestions that enhance their travel experience. The main focus of this work is on the use of fuzzy logic as the basis for the rec­ommendation system, which allows for a more flexible and accurate suggestion mechanism that takes into account uncertainties and the diversity of user preferences. The methodology proposed by the authors is based on applying a fuzzy content model to the described problems as an effective extension of the collaborative model. The article describes a method for implementing the recommendation system algorithm, lists the technical tools used to imple­ment the application, presents an activity diagram of the working application, describes the process of searching, preparing, and annotating data used in the working application. The presented software and methodological tools help to solve problems associated with the clear categorization of tourist objects within traditional types of tourism, arising from the broad classification of tourist objects, thereby improving the quality of the tourist experience.

Keywords: tourism, tourism optimization, recommendation systems, collaborative filtering, fuzzy logic, mobile development.

pp. 425—433

For citation:
Kotsyuba I. Y., Blinov I. S. Tourism Application Development with a Recommendation System based on Fuzzy Logic, Programmnaya Ingeneria, 2024, vol. 15, no. 8. pp. 425—433. DOI: 10.17587/prin.15.425-433. (in Russian).

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