DocumentCode :
1823095
Title :
Link prediction in human mobility networks
Author :
Yang Yang ; Chawla, Nitesh V. ; Basu, Prithwish ; Prabhala, Bhaskar ; La Porta, Tom
Author_Institution :
Dept. of Comput. Sci., Univ. of Notre Dame, Notre Dame, IN, USA
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
380
Lastpage :
387
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.
Keywords :
social networking (online); future mobility topology; human mobility networks; human mobility patterns; link prediction technology; urban planning; Conferences; Facebook; Network topology; Protocols; Time series analysis; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON
Type :
conf
Filename :
6785734
Link To Document :
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