Location Recommendation Based on Social Trust (original) (raw)
2017 13th International Conference on Semantics, Knowledge and Grids (SKG), 2017
Abstract
Social network has lately shown an important impact in both scientific and social societies and is considered a highly weighted source of information nowadays. Due to its noticeable significance, several research movements were introduced in this domain including: Location-Based Social Networks (LBSN), Recommendation Systems, Sentiment Analysis Applications, and many others. Location Based Recommendation systems are among the highly required applications for predicting human mobility based on users' social ties as well as their spatial preferences. In this paper we introduce a trust based recommendation algorithm that addresses the problem of recommending locations based on both users' interests as well as social trust among users. In our study we use two real LBSN, Gowalla and Brightkite that include the social relationships among users as well as data about their visited locations. Experiments showing the performance of the proposed trust based recommendation algorithm are also presented.
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