Paper Info
Title
Link prediction in human mobility networks
Abstract
The understanding of how humans move is a long-standing 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.
Year
DOI
Venue
2013
10.1145/2492517.2492656
ASONAM
Keywords
Field
DocType
link prediction,human mobility patterns,urban planning,macroscopic perspective,individual mobility behavior,human mobility behavior,human mobility network,human behavior,future mobility topology,human mobility pattern,microscopic perspective,network science,social networking (online),link prediction technology,humans move,human mobility networks,virtual worlds
Data science,Network science,Individual mobility,Metaverse,Computer science,Mobility model,Urban planning,Artificial intelligence,Location prediction,Machine learning
Conference
Citations 
PageRank 
References 
3
0.39
14
Authors
5
Name
Order
Citations
PageRank
Yang Yang120710.09
Nitesh Chawla27257345.79
Prithwish Basu370352.93
Bhaskar Prabhala451.14
Thomas La Porta580191.33