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Detecting expectation-based spatio-temporal clusters formed during opportunistic sensing

 
: Orlinski, M.; Filer, N.

:

Institute of Electrical and Electronics Engineers -IEEE-:
IEEE International Conference on Pervasive Computing and Communication workshops, PerCom Workshops 2014 : Budapest, Hungary, 24 - 28 March 2014
Piscataway, NJ: IEEE, 2014
ISBN: 978-1-4799-2737-1
ISBN: 978-1-4799-2736-4
S.581-586
International Conference on Pervasive Computing and Communication (PerCom) <12, 2014, Budapest>
International Workshop on Social and Community Intelligence (SCI) <2, 2014, Budapest>
Englisch
Konferenzbeitrag
Fraunhofer IAIS ()

Abstract
Detecting clusters in the encounter graphs generated from reality mining data is one way of detecting the social and spatial relationships of participants. However, many of the existing clustering algorithms do not factor in the time since encounters, and can only be used to describe a single aggregated snapshot of the data. This paper describes a spatio-temporal clustering technique which has been used to reveal the transient communities within the data.

: http://publica.fraunhofer.de/dokumente/N-301447.html