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Author Yohann Chasseray; Anne-Marie Barthe-Delanoë; Stéphane Négny; Jean-Marc Le Lann
Title Automated unsupervised ontology population system applied to crisis management domain Type Conference Article
Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021
Volume Issue Pages (down) 968-981
Keywords Automated knowledge extraction, Crisis management systems, Ontologies, Experience feedback exploitation, Background knowledge acquisition
Abstract As crisis are complex systems, providing an accurate response to an ongoing crisis is not possible without ensuring situational awareness. The ongoing works around knowledge management and ontologies provide relevant and machine readable structures towards situational awareness and context understanding. Many metamodels, that can be derived into ontologies, supporting the collect and organization of crucial information for Decision Support Systems have been designed and are now used on specific cases. The next challenge into crisis management is to provide tools that can process an automated population of these metamodels/ontologies. The aim of this paper is to present a strategy to extract concept-instance relations in order to feed crisis management ontologies. The presented system is based on a previously proposed generic metamodel for information extraction and is applied in this paper to three different case studies representing three different crisis namely Ebola sanitarian crisis, Fukushima nuclear crisis and Hurricane Katrina natural disaster.
Address Laboratoire de Génie Chimique, Universitéde Toulouse, CNRS, INPT, UPS, Toulouse,France; Centre Génie Industriel, Université deToulouse, IMT Mines Albi, France; Laboratoire de Génie Chimique, Universitéde Toulouse, CNRS, INPT, UPS, Toulouse,France; Laborat
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-61-5 ISBN Medium
Track Visions for Future Crisis Management Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management
Notes yohann.chasseray@inp-toulouse.fr Approved no
Call Number ISCRAM @ idladmin @ Serial 2389
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Author Nada Matta; Paul Henri Richard; Alain Hugerot; Theo Lebert
Title Experience Feedback Capitalization of Covid-19 Management in Troyes city Type Conference Article
Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022
Volume Issue Pages (down) 311-319
Keywords Experience feedback; MASK method; COVID19 crisis Management; actors’ relations formalization
Abstract All countries have to face the COVID’19 pandemic and its heavy consequences. This sanitary crisis differs from all others in terms of the quick spread of contaminations, the high number of deaths (more than 5,5 Million globally and 123,893 in France) and the accrued number of patients hospitalized and induced in intensive care units. All sanitary procedures have proven to be inadequate. Several actors at different levels, whether international, European, national and local, as well as at the level of public and private organizations have been involved in the management of this type of crisis. These actors deal with different aspects of it, i.e., health, people protection, and economic and social situations. Existing procedures revealed a big lack in the relationships between different local and departmental actors. We did a number of interviews with strategic actors addressing the COVID’19 crisis in the City of Troyes. The objective of these interviews is to identify lessons learned from their experience feedback about relational problems and modifications needed. We present in this paper the first results of this study.
Address University of Technology of Troyes; University of Technology of Troyes; Hospital of Simon Weil of Troyes; Orange Lab
Corporate Author Thesis
Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium
Track AI and Intelligent Systems for Crises and Risks Expedition Conference
Notes Approved no
Call Number ISCRAM @ idladmin @ Serial 2420
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Author Mohamed Sediri; Nada Matta; Sophie Loriette; Alain Hugerot
Title Crisis clever, a system for supporting crisis managers Type Conference Article
Year 2013 Publication ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2013
Volume Issue Pages (down) 261-265
Keywords Hardware; Collaborative approach; Crisis management; Experience and situations representations; Experience feedback; Information systems
Abstract Crisis management is a special type of collaborative approach in which the actors are subject to an uninterrupted stress. It is a quite significant issue because the consequences of crises can bring huge damages (human and economic loses). In order to learn from expertise and reduce consequences, we present in this paper our first results related to the definition of structure and interfaces in order to handle experience of crisis management. The project aims to define the CCS (Crisis Clever System) as a decision making environment based on the emergency experience feedback (Experience representation and use).
Address ICD, Tech-CICO, Université de Technologie de Troyes, France; Emergency Department, PhMD SAMU 10, Troyes, France
Corporate Author Thesis
Publisher Karlsruher Institut fur Technologie Place of Publication KIT; Baden-Baden Editor T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9783923704804 Medium
Track Decision Support Systems Expedition Conference 10th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 932
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