• DocumentCode
    652613
  • Title

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

  • Author

    Negre, Elsa

  • Author_Institution
    LAMSADE, Univ. Paris-Dauphine, Paris, France
  • fYear
    2013
  • fDate
    28-30 Oct. 2013
  • Firstpage
    713
  • Lastpage
    718
  • Abstract
    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.
  • Keywords
    alarm systems; emergency management; recommender systems; crisis management; early warning system; information communication systems; knowledge based recommender system; physical world; response system; Alarm systems; Context; Crisis management; Hazards; Motion pictures; Recommender systems; Vectors; Crisis management; Decision support; Early warning systems; Experience; Knowledge; Recommender systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2013 Eighth International Conference on
  • Conference_Location
    Compiegne
  • Type

    conf

  • DOI
    10.1109/3PGCIC.2013.121
  • Filename
    6681317