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Constraint-based recommender system for crisis management simulations

Le Ngoc, Luyen; Zhong, Jinfeng; Negre, Elsa; Abel, Marie-Hélène (2023), Constraint-based recommender system for crisis management simulations, Proceedings of the 56th Hawaii International Conference on System Sciences, University of Hawaii at Manoa : Honolulu, p. 1778-1789

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0174.pdf (532.2Kb)
Type
Communication / Conférence
External document link
https://hdl.handle.net/10125/102854
Date
2023
Conference title
The 56th Hawaii International Conference on System Sciences
Conference date
2023-01
Conference city
Honolulu
Conference country
United States
Book title
Proceedings of the 56th Hawaii International Conference on System Sciences
Publisher
University of Hawaii at Manoa
Published in
Honolulu
ISBN
978-0-9981331-6-4
Pages
1778-1789
Metadata
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Author(s)
Le Ngoc, Luyen cc
Heuristique et Diagnostic des Systèmes Complexes [Compiègne] [Heudiasyc]
Vivocaz
Zhong, Jinfeng
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Negre, Elsa
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abel, Marie-Hélène cc
Heuristique et Diagnostic des Systèmes Complexes [Compiègne] [Heudiasyc]
Abstract (EN)
In the context of the evacuation of populations, some citizens/volunteers may want and be able to participate in the evacuation of populations in difficulty by coming to lend a hand to emergency/evacuation vehicles with their own vehicles. One way of framing these impulses of solidarity would be to be able to list in real-time the citizens/volunteers available with their vehicles (land, sea, air, etc.), to be able to geolocate them according to the risk areas to be evacuated, and adding them to the evacuation/rescue vehicles. Because it is difficult to propose an effective real-time operational system on the field in a real crisis situation, in this work, we propose to add a module for recommending driver/vehicle pairs (with their specificities) to a system of crisis management simulation. To do that, we chose to model and develop an ontology-supported constraint-based recommender system for crisis management simulations.
Subjects / Keywords
Disaster Information; Resilience for Emergency and Crisis Technologies; Crisis management; Decision support system; Ontologies; Recommender system

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