Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining

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dc.contributor.authorLê, Ngoc Luyen
dc.contributor.authorAbel, Marie-Hélène
dc.contributor.authorNegre, Elsa
dc.date.accessioned2023-12-26T18:38:02Z
dc.date.available2023-12-26T18:38:02Z
dc.date.issued2024-01-03
dc.identifier.doihttps://doi.org/10.24251/HICSS.2024.261
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.othereb6078db-a514-443d-b35e-a08ddd890c92
dc.identifier.urihttps://hdl.handle.net/10125/106640
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDisaster Information, Resilience, for Emergency and Crisis Technologies
dc.subjectcrisis management
dc.subjectknowledge representation
dc.subjectontology
dc.subjectsemantic similarity
dc.titleRecognizing Similar Crises through the Application of Ontology-based Knowledge Mining
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractRecognizing and learning from similar crisis situations is crucial for the development of effective response strategies. This study addresses the challenge of identifying similarities within a wide range of crisis-related information. To overcome this challenge, we employed an ontology-based crisis situation knowledge base enriched with crisis-related information. Additionally, we implemented a semantic similarity measure to assess the degree of similarity between crisis situations. Our investigation specifically focuses on recognizing similar crises through the application of ontology-based knowledge mining. Through our experiments, we demonstrate the accuracy and efficiency of our approach to recognizing similar crises. These findings highlight the potential of ontology-based knowledge mining for enhancing crisis recognition processes and improving overall crisis management strategies.
dcterms.extent10 pages
prism.startingpage2106

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