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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.03770 |
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| _version_ | 1866913188768907264 |
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| author | Le, Ngoc Luyen Abel, Marie-Hélène Negre, Elsa |
| author_facet | Le, Ngoc Luyen Abel, Marie-Hélène Negre, Elsa |
| contents | Recognizing 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_03770 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining Le, Ngoc Luyen Abel, Marie-Hélène Negre, Elsa Information Retrieval Recognizing 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. |
| title | Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2401.03770 |