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Towards a Knowledge (Experience)-Based Recommender System for Crisis Management

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SNDE_2013_Elsa.pdf (360.4Kb)
Date
2013
Dewey
Informatique générale
Sujet
Recommender system; Crisis management; Decision support; Early warning systems; Experience; Knowledge
DOI
http://dx.doi.org/10.1109/3PGCIC.2013.121
Conference name
Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)
Conference date
10-2013
Conference city
Compiègne
Conference country
France
Book title
2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)
Publisher
IEEE
Publisher city
Piscataway, NJ
Year
2013
ISBN
978-0-7695-5094-7
URI
https://basepub.dauphine.fr/handle/123456789/15643
Collections
  • LAMSADE : Publications
Metadata
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Author
Negre, Elsa
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Type
Communication / Conférence
Item number of pages
713-718
Abstract (EN)
An early warning system can be defined as a chain of information communication systems comprising sensor, detection, decision, and broker subsystems, in the given order, working in conjunction, forecasting and signaling disturbances adversely affecting the stability of the physical world, and giving sufficient time for the response system to prepare resources and response actions to minimize the impact on the stability of the physical world. In this paper, we present a framework for a recommender system for crisis management. This framework uses the actions already implemented to manage former crises to enhance the management of a given crisis. The main idea is to recommend the actions already implemented in those former crises that are similar (the similarity between two crises is based on some indicators such as the gap (hurricane, tsunami) as the actions to be implemented. Finally, this paper proposes to exploit the knowledge gained from past experiences to make the best decision (i.e. the best actions to implement) in order to better manage a crisis ready to occur.

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