Knowledge, semantics and AI for risk and crisis management (English)
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In:
Journal of Contingencies and Crisis Management
;
28
, 3
;
174-177
;
2020
- Article (Journal) / Electronic Resource
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Title:Knowledge, semantics and AI for risk and crisis management
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Contributors:De Nicola, Antonio ( author ) / Karray, Hedi ( author ) / Kejriwal, Mayank ( author ) / Matta, Nada ( author )
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Published in:Journal of Contingencies and Crisis Management ; 28, 3 ; 174-177
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Publisher:
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Publication date:2020-09-01
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Size:4 pages
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ISSN:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents – Volume 28, Issue 3
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 173
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Issue Information| 2020
- 174
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Knowledge, semantics and AI for risk and crisis managementDe Nicola, Antonio / Karray, Hedi / Kejriwal, Mayank / Matta, Nada et al. | 2020
- 178
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A comprehensive system for semantic spatiotemporal assessment of risk in urban areasColetti, Alex / De Nicola, Antonio / Di Pietro, Antonio / La Porta, Luigi / Pollino, Maurizio / Rosato, Vittorio / Vicoli, Giordano / Villani, Maria Luisa et al. | 2020
- 194
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Improving emergency preparedness to cascading disasters: A case‐driven risk ontology modellingYu, Feng / Fan, Bo / Li, Xiangyang et al. | 2020
- 215
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Data‐driven model for river flood forecasting based on a Bayesian network approachBoutkhamouine, Brahim / Roux, Hélène / Pérés, François et al. | 2020
- 228
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A mathematical model for the diffusion of emergency warning messages during CBRNe emergenciesD’Arienzo, Marco / Di Paolo, Ferruccio / Chiacchiararelli, Laura / Malizia, Andrea / Indovina, Luca et al. | 2020
- 240
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Do intentions indicate actual behaviour? A comparison between scenario‐based experiments and real‐time observations of warning responseWeyrich, Philippe / Scolobig, Anna / Walther, Florian / Patt, Anthony et al. | 2020
- 251
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Using deep learning and social network analysis to understand and manage extreme floodingRomascanu, Andrei / Ker, Hannah / Sieber, Renee / Greenidge, Sarah / Lumley, Sam / Bush, Drew / Morgan, Stefan / Zhao, Rosie / Brunila, Mikael et al. | 2020
- 262
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What happens where during disasters? A Workflow for the multifaceted characterization of crisis events based on Twitter dataKersten, Jens / Klan, Friederike et al. | 2020
- 281
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Improving automated crisis detection via an improved understanding of crisis language: Linguistic categories in social media crisesBorden, Jonathan / Zhang, Xiaochen Angela / Hwang, Jooyun et al. | 2020
- 291
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An AI framework and a metamodel for collaborative situations: Application to crisis management contextsBenaben, Frederick / Fertier, Audrey / Montarnal, Aurélie / Mu, Wenxin / Jiang, Zheng / Truptil, Sebastien / Barthe‐Delanoë, Anne‐Marie / Lauras, Matthieu / Mace‐Ramete, Guillaume / Wang, Tiexin et al. | 2020
- 307
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Handling effective communication to support awareness in rescue operationsChehade, Samer / Matta, Nada / Pothin, Jean‐Baptiste / Cogranne, Remi et al. | 2020
- 324
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PROMES: An ontology‐based messaging service for semantically interoperable information exchange during disaster responseElmhadhbi, Linda / Karray, Mohamed‐Hedi / Archimède, Bernard / Otte, J. Neil / Smith, Barry et al. | 2020
- 339
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AI‐Powered mental health chatbots: Examining users’ motivations, active communicative action and engagement after mass‐shooting disastersCheng, Yang / Jiang, Hua et al. | 2020
- 355
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Participatory Bayesian modelling for sustainable and efficient river restoration projects: Feedback from the case study of the Gave de Pau River, Hautes‐Pyrénées, FranceYassine, Rabab / Pérès, François / Frysou, Olivier / Roux, Hélène / Cassan, Ludovic et al. | 2020