Design And Implementation Of Intelligent Tourism Recommendation System Based On Weighted Association Rule Mining

Wisdom tour which is base of the traditional tourist information service is becomingmore and more popular. Stimulated by popular demand, a number of travel servicescompany has introduced a personalized wisdom travel services and created a distinctivetourism brand. Wisdom travel which is a user-friendly travel will be integrated with richtourism information. Through the wisdom of management,information is close to everytraveler. Thanks to the development of net and rapid information transfer rate,smarttravel system has a very strong ability to integrate information. the recommended way inwisdow travel is still mainly traditional classification recommended. In today’s diversetourism resources, the recommended way has been unable to meet the needs of users..Forlack of wisdom tourist attractions recommending,this paper presents an intelligentrecommendation implementation. Through the analysis of user interaction behaviordata,we can get users’ degree of interest and degree of recognition in browsedattractions.On this basis,the use of multiple minimum supports weighted fp-treealgorithm to dig out potential modes.These modes are recommended as the basis forattractions. Compared with the traditional classification recommendation, associationrules recommended to better meet the needs of different groups. The system providespersonalized attractions recommended characteristics for different users. Throughcontinuous feedback of user behavior data, gradually positioning information to theattractions of interest to the user.After testing, the system can well meet the needs ofusers at the attractions recommended.