Open AccessA PERSONALIZED TRAVEL RECOMMENDER SYSTEM USING FUZZY ANALYTIC HIERARCHY PROCESS
Author(s) -
Ily Amalina Ahmad Sabri,
Noor Maizura Mohamad Noor,
Noraida Haji Ali,
Fathilah Ismail
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.46754/gtc.2021.11.011
Subject(s) - computer science , recommender system , tourism , analytic hierarchy process , decision support system , ranking (information retrieval) , fuzzy logic , benchmark (surveying) , process (computing) , variety (cybernetics) , operations research , risk analysis (engineering) , machine learning , data mining , artificial intelligence , business , engineering , geodesy , political science , geography , law , operating system
Information and communication technologies have deep implications for the tourism industry. This combination of devices is being used extensively in an excessive variety of functions and numerous applications. On the other hand, tourism has become an extremely dynamic system. The globalisation enabled by technological development and budget travel has greatly increased competition. Decision support systems (DSS) can play an important role within organisations and assist people who manage tourist destinations. The main intention of this research paper is to see how to apply Decision Support Systems (DSS) to the tourism industry. It aims to establish a personalised interactive travel recommender system that can be shared and integrated easily in order to work as a proof of concept for the decision to provide the tourism sector with interactive decision support systems. Specifically, the study aims to achieve the following objectives which are to evaluate and measure criteria and alternatives to performance, to analyse the ranking of criteria and alternatives and to recommend tourist attractions in terms of islands, accommodation, activities and etc. based on the travellers’ budget constraints. The evaluation module enables experts to evaluate and consider alternatives to the small islands to benchmark the islands’ performance. An analysis module will provide reports for performance of criteria and alternatives based on a “Best Non-fuzzy Performance” basis. A risk analysis model for the travel recommender system using a fuzzy set approach has been proposed and incorporated into a Fuzzy Decision Support System (FDSS). This study presents fuzzy-AHP as a proposed method to apply to decision-making with social attributes. A web-based prototype Decision Support System (DSS) has been designed and developed in order to prove the objectives.