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Geospatial Web Mining for Emergency Management
Fritz, Christian
;
Kirschner, Christian
;
Reker, Daniel
;
Wisplinghoff, Andre
;
Paulheim, Heiko
;
Probst, Florian
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URL:
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https://madoc.bib.uni-mannheim.de/33056
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Additional URL:
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http://www.heikopaulheim.com/documents/giscience_2...
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URN:
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urn:nbn:de:bsz:180-madoc-330567
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Document Type:
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Conference presentation
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Year of publication:
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2010
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Conference title:
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GIScience 2010: Sixth International Conference on Geographic Information Science
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Location of the conference venue:
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Zurich, Switzerland
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Date of the conference:
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14.-17.9.2010
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Information Systems V: Web-based Systems (Bizer 2012-)
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Subject:
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004 Computer science, internet
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Abstract:
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Emergency management is a domain where information has to be gathered,
aggrega
ted, and visualized dynamically and quickly. By providing the right
information at the right time, the chaos phase between the occurrence of a disaster and
the start of well
-
organized relief measures can be significantly shortened (Paulheim et
al. 2009).
T
he information needed in an emergency scenario can be quite diverse. For
example, a person planning an evacuation may need to know about companies that can
transport people, and places that can serve as emergency shelters. For the first, bus and
taxi compa
nies, logistics companies as well as rental car providers may be taken into
account. The latter may include hotels and schools as well as sports arenas and concert
venues.
Although all this information is available on the web, it cannot be easily accessed.
Since such non
-
trivial categories such as
buildings that can serve as emergency shelter
are not sharply defined, one cannot simply enter
emergency shelter
into Google and
retrieve a list of emergency shelters. Instead, lots of subsequent manual searches h
ave
to be performed, and the results have to be aggregated by hand. Visual exploration is
even more difficult.
While several emergency management tools exist (cf. (Paulheim et al. 2009) for a
survey), this concern has not been addressed in this context yet. In this paper, we
introduce a prototype which allows for a
-
priori crawling the web for relevant
information on objects belonging to non
-
trivial categories and provide the aggregated
results as an OGC compliant web feature service for visual exploration.
|
 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 | Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt. |
 Search Authors in
BASE:
Fritz, Christian
;
Kirschner, Christian
;
Reker, Daniel
;
Wisplinghoff, Andre
;
Paulheim, Heiko
;
Probst, Florian
Google Scholar:
Fritz, Christian
;
Kirschner, Christian
;
Reker, Daniel
;
Wisplinghoff, Andre
;
Paulheim, Heiko
;
Probst, Florian
ORCID:
Fritz, Christian, Kirschner, Christian, Reker, Daniel, Wisplinghoff, Andre, Paulheim, Heiko  ORCID: https://orcid.org/0000-0003-4386-8195 and Probst, Florian
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