Tourist spot recommendation system using fuzzy inference system

A fuzzy logic based recommender system is proposed in this research that uses Fuzzy Inference System (FIS) to recommend tourist spots to travelers. The system keeps a database containing tourist locations and their respective information as well as some specific data which is used as parameters for the inference system. The system prompts user to give their desired location type(s) that they wish to visit, their budget, the number of people going on the trip, and other defined parameters which are used in the inference system. We have decided to limit the compound location type to two for simplicity of the calculation. Besides, a tourist is not normally interested in more than two location types. In addition to that, we will suggest the user some other places of different types around the selected locations which they may wish to visit during their stay. Once the input is taken, the system will fetch corresponding data from the database, fuzzify the metadata and pass it to the fuzzy recommendation engine. The recommendation engine will calculate and assign a crisp value to each location as an output. Then the list is sorted in a descending order and the top locations that satisfy most of the user's defined preferences are recommended to the user.