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Automated support for dynamic information distribution in incident management
Niels Netten
Maarten Van Someren
B. Van de Walle, M.T.
For all emergency response personnel involved in crisis situations it is essential to timely acquire all information critical to their task performance. However, in practice errors occur in the distribution of information between these collaborating actors leading to mistakes and subsequently more damage to the situation. In this paper we present a prototype system for dynamic information distribution able to support the information flow between collaborating crisis actors. The system has been evaluated by means of simulated experiments that use data from a real incident scenario. The results indicate that automated support by means of Machine Learning method works well. Especially, when actor work context features are included, then the performance on selecting and distributing relevant information is high. Furthermore, actors acquire relevant information much faster making group communication much more efficient.
urn:ISBN:9090206019; 9789090206011
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Automated%20support%20for%20dynamic%20information%20distribution%20in%20incident%20management&stitle=ISCRAM%202006&issn=2411-3387&isbn=9090206019%3B%209789090206011&date=2006&spage=230&epage=237&aulast=Niels%20Netten&au=Maarten%20Van%20Someren&pub=Royal%20Flemish%20Academy%20of%20Belgium&place=Newark%2C%20NJ&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=807
citekey:NielsNetten+MaartenVanSomeren2006
citation:Niels Netten, & Maarten Van Someren. (2006). Automated support for dynamic information distribution in incident management. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 230-237). Newark, NJ: Royal Flemish Academy of Belgium.
2006
ConferencePaper
text
Artificial intelligence
Information systems
Adaptive information
Automated support
Dynamic information
Emergency response personnels
Group communications
Incident Management
Machine learning methods
Simulated experiments
Learning systems
file:http://idl.iscram.org/files/netten/2006/807_Netten+VanSomeren2006.pdf
Royal Flemish Academy of Belgium
English
2411-3387
Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management
2006
230
237
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