Contextual Feature Analysis to Improve Link Prediction for Location Based Social Networks

In recent years, people started to communicate, interact, maintain relationship and share data (image, video, note, location, etc.) with their acquaintances through varying online social network sites. Online social networks with location and time sharing/interaction among people are called Location Based Social Networks (LBSNs). Link prediction in social networks aims at predicting future possible links for representing the real life relations better. In this work, we studied the link prediction problem and proposed new contextual features that improve the link prediction performance for LBSNs.

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