Prototype of a tourism recommender system

When making a trip most of tourist used the Web to find information, encountering a problem that has been called “information overload”. In a tourism website, “coexist” several services: accommodation, transportation, cultural activities, travel agencies, and others. Usually the tourist has to search for hotels, transportation, restaurants separately and find the best combination of services to build a trip. This paper presents a prototype of a recommender system in the province of San Juan, Argentina, to recommend tourist packages based on preferences and interest of each user. Artificial Intelligence techniques are used to filter and customize the information.