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Author:

Wang, Hui (Wang, Hui.) | Zhong, Ning (Zhong, Ning.) | Huang, Zhisheng (Huang, Zhisheng.) | Huang, Jiajin (Huang, Jiajin.) | Zhou, Erzhong (Zhou, Erzhong.) | Du, Runqiang (Du, Runqiang.)

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EI Scopus

Abstract:

Nowadays, mobile phones are often used as an attractive option for large-scale sensing of human behavior, providing a source of real and reliable data for urban computing. As it is known to all, a user's behavior often happened at some places where the user stayed over a certain time interval for a trip. For understanding a user's behavior effectively, we need to detect the places where the user stayed over a certain time interval and we call these places stay areas. In this paper, we propose a method for detecting the stay areas from a user's mobile phone data. The proposed method can tackle the complicated situations that the general method cannot deal with effectively. Through experimental evaluation, the proposed method is shown to deliver excellent performance. © 2014 Springer International Publishing.

Keyword:

Cellular telephones Behavioral research

Author Community:

  • [ 1 ] [Wang, Hui]International WIC Institute, Beijing University of Technology, Beijing, China
  • [ 2 ] [Zhong, Ning]International WIC Institute, Beijing University of Technology, Beijing, China
  • [ 3 ] [Zhong, Ning]Dept. of Life Science and Informatics, Maebashi Institute of Technology, Maebashi, Japan
  • [ 4 ] [Huang, Zhisheng]International WIC Institute, Beijing University of Technology, Beijing, China
  • [ 5 ] [Huang, Zhisheng]Dept. of Computer Science, Vrije University of Amsterdam, Amsterdam, Netherlands
  • [ 6 ] [Huang, Jiajin]International WIC Institute, Beijing University of Technology, Beijing, China
  • [ 7 ] [Zhou, Erzhong]International WIC Institute, Beijing University of Technology, Beijing, China
  • [ 8 ] [Du, Runqiang]International WIC Institute, Beijing University of Technology, Beijing, China

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ISSN: 0302-9743

Year: 2014

Volume: 8610 LNCS

Page: 336-346

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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