Access and mobility of wireless PDA users
ACM SIGMOBILE Mobile Computing and Communications Review
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
The diameter of opportunistic mobile networks
CoNEXT '07 Proceedings of the 2007 ACM CoNEXT conference
The Time-Series Link Prediction Problem with Applications in Communication Surveillance
INFORMS Journal on Computing
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting place features in link prediction on location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Friendship and mobility: user movement in location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic topic models with biased propagation on heterogeneous information networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Contextual conditional models for smartphone-based human mobility prediction
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
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The understanding of how humans move is a longstanding challenge in the natural science. An important question is, to what degree is human behavior predictable? The ability to foresee the mobility of humans is crucial from predicting the spread of human to urban planning. Previous research has focused on predicting individual mobility behavior, such as the next location prediction problem. In this paper we study the human mobility behaviors from the perspective of network science. In the human mobility network, there will be a link between two humans if they are physically proximal to each other. We perform both microscopic and macroscopic explorations on the human mobility patterns. From the microscopic perspective, our objective is to answer whether two humans will be in proximity of each other or not. While from the macroscopic perspective, we are interested in whether we can infer the future topology of the human mobility network. In this paper we explore both problems by using link prediction technology, our methodology is demonstrated to have a greater degree of precision in predicting future mobility topology.