An Individual Service Recommendation Model Based on Social Network and Location Awareness

With the rapid development of Web technology and mobile devices, it is necessary to provide efficient models for service recommendation. In connection with the problems of existing systems and LBS (Location Based Service), we propose a model composed of three modules. In social network module, we detect community from the social network, classify users by computing the shortest length and filter users according to the destination. The location awareness module collects the history trace of users with the positioning algorithm based on mobile anchor node. In the module of LBS, we unify the description of user traces using locations obtained from extracting and clustering the key points. After that, we compute the relevance between two locations to realize the location recommendation service. At last, we provide some simulations to verify the validity and enforceability of the model we proposed.