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Multidimensional report analysis in urban incident management

 
: Fotouhi Tehrani, Pouyan; Pfennigschmidt, Stefan; Kriegel, Ulrich; Billig, Andreas; Fuchs-Kittowski, Frank; Meissen, Ulrich

:
Postprint urn:nbn:de:0011-n-4845151 (3.3 MByte PDF)
MD5 Fingerprint: 54703573be0f457ccb500922e07d0edd
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Erstellt am: 22.2.2018


Institute of Electrical and Electronics Engineers -IEEE-:
4th International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2017. Proceedings : University of Münster, Germany, December 11 to December 13, 2017
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5386-2553-8
ISBN: 978-1-5386-2554-5
7 S.
International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) <4, 2017, Münster>
European Commission EC
H2020; 653747; City.Risks
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer FOKUS ()

Abstract
In urban incidents and crises, accurate and timely information can be crucial to manage critical situations. The exponential growth of crowd sourced data has given means to access vast amounts of information on a real-time basis. However, this has complicated the task of analyzing ongoing events as the effort needed to filter relevant from irrelevant information has exponentially grown. This paper proposes a multidimensional analysis method of processing high influx of crowd sourced incident reports and creating processable pieces of information by filtering what's irrelevant and clustering what belongs together in a highly efficient way. Spatial, temporal, and semantic dimensions of an incident report constitute a basis which is taken advantage of in this work to ease the tasks which are undertaken manually in operation centers and alike.

: http://publica.fraunhofer.de/dokumente/N-484515.html