Process Recommendation using Context in Crisis Management: Application to Flood Management

Hanane Ariouat, Eric Andonoff, Chihab Hanachi

2018

Abstract

This paper addresses process recommendation in crisis management from relevant facts observed in the field and business knowledge of actors involved in crisis resolution. Facts observed correspond to damage or risk while business knowledge of crisis actors, i.e. actors involved in crisis resolution, corresponds to actions these actors can perform in the field to reduce the crisis and to strategies for using these actions according to the context. The approach recommended in the paper filters facts observed with strategies modelled taking into account the current situation and dynamically builds process models dealing with these facts. Built process models, represented as BPMN diagrams, define actions crisis actors have to perform in the field along with the coordination of these actions. As several strategies are possible to deal with facts, several process models are recommended, each being labelled with its adequacy with the current situation. This paper presents the meta-model for facts and business knowledge modelling along with the recommended approach for process recommendation. Flood of the Loire serves as a case study for process recommendation illustration.

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Paper Citation


in Harvard Style

Ariouat H., Andonoff E. and Hanachi C. (2018). Process Recommendation using Context in Crisis Management: Application to Flood Management.In - ICE-B, ISBN , pages 0-0. DOI: 10.5220/0006895201110122


in Bibtex Style

@conference{ice-b18,
author={Hanane Ariouat and Eric Andonoff and Chihab Hanachi},
title={Process Recommendation using Context in Crisis Management: Application to Flood Management},
booktitle={ - ICE-B,},
year={2018},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006895201110122},
isbn={},
}


in EndNote Style

TY - CONF

JO - - ICE-B,
TI - Process Recommendation using Context in Crisis Management: Application to Flood Management
SN -
AU - Ariouat H.
AU - Andonoff E.
AU - Hanachi C.
PY - 2018
SP - 0
EP - 0
DO - 10.5220/0006895201110122