A fuzzy model for selecting travel services to produce personalized offers to Internet users. (December 2020)

• Record Type: Journal Article
• Authors: Shpolianskaya, I; Dolzhenko, A; Stepanov, N; Potapov, L
• Is Part Of: Journal of physics. Volume 1703(2020)
• Publication Date: 2020-12
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1703/1/012014
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: With the spread of information technologies in the field of tourism and the emergence of a specific sector of e-tourism, an increasingly urgent problem is not the traditional search for relevant information on the Internet, but the search for personally oriented, personalized information adapted to the individual needs of specific users. The main issue in e-tourism is to determine the most suitable tourist resources from the many available for use by a particular user. Recommender systems in e-tourism provide the mechanism of satisfying customized users' requirements by supplying them with adequate information about travel resources and services. The implementation of tourist goals can be carried out by a variety of different combinations of travel services. The optimal selection of services is a complex multi-alternative task due to the lack of data about the quality of services and the complexity of the description of user preferences. The paper considers the possibility of using fuzzy logic to the development of the e-tourism support system. Based on user profile data, web services that provide information about travel services, and ratings of services by other users, the system evaluates various alternatives of service's composition and selects the recommended objects (hotels, flights, restaurants, car rental, museums, etc.). The service-oriented paradigm has been proposed to model the composition of tourism services, and fuzzy logic is used to evaluate the quality and compliance of tourism services with user requests and preferences. The proposed fuzzy logic-based approach analyzes the quality of travel services for personal recommendations to the tourist. The proposed model can provide decision support to users to select the most appropriate travel services and to plan a trip.