A Recommender System Combining Social Networks for Tourist Attractions

The fast development of Web technologies has introduced a world of big data. How efficiently and effectively to retrieve the information from the ocean of data that the users really want is an important topic. Recommendation systems have become a popular approach to personalized information retrieval. On the other hand, social media have quickly entered into your life. The information from social networks can be an effective indicator for recommender systems. In this paper we present a recommendation mechanism which calculates similarity among users and users´ trustability and analyzes information collected from social networks. To validate our method an information system for tourist attractions built on this recommender system has been presented. We further evaluate our system by experiments. The results show our method is feasible and effective.