Research On Personalized Tourist Attraction Recommendation System Based On Spatial Data Mining

With the development of economy and society, material products can not meet people's needs, spiritual products into public view. Tourism had development as a modern spiritual and physical dual meet,then the tourism industry ushered in the golden period of rapid development. Especially in the information age, The timeliness and practicability of the Internet breaks through the limitation of the space and the block of information, which bring tourists satisfaction.The key technology is the development of GPS technology and mobile Internet, generated a lot of location-based services, which gives the user a richer experience, but also to promote the participation of users to share the fun. Some pictures with location tag sharing site has been welcomed by customers, and generated a lot of photos including Geo-location shooting time, labels. Through these photos with Geo-tag information collection mining, we can get the city's attractions area and the user preferences and other information of interest, and we can use this information to provide users with personalized recommendations on places.In this paper, the photos with geographic tags by spatial clustering algorithm, and tap the city's attractions area attractions and user preferences, context information combined with the time the photo was taken, giving users recommend interesting sights. The research work done in this paper mainly includes:(1) Analysis of the research status of spatial data and personalized travel recommendation system; the process and key technologies of spatial data mining and personalized recommendation are summarized presentation.(2) Through the DBSCAN(density based spatial clustering of applications with noise) clustering algorithm to deal with photos.Extraction area attractions, points of interest and create user interest matrix, area attractions heat vector.(3) Based on user preference, time, context, popular attractions, proposed BIPM (Based on Interest Popularity And Month) personalized tourist attractions of recommendation algorithm. And built personalized Attractions model.(4) Based the model of personalized Attractions, designed and implemented personalized Attractions system, and thus recommended for users interested in tourist attractions. The system uses the list and marked on the map show the form of Baidu recommended result.