Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining
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...
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| creator | Le, Ngoc Luyen Abel, Marie-Hélène Negre, Elsa |
| description | 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. |
| doi_str_mv | 10.48550/arxiv.2401.03770 |
| format | Article |
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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.</description><identifier>DOI: 10.48550/arxiv.2401.03770</identifier><language>eng</language><subject>Computer Science - Information Retrieval</subject><creationdate>2024-01</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2401.03770$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2401.03770$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Le, Ngoc Luyen</creatorcontrib><creatorcontrib>Abel, Marie-Hélène</creatorcontrib><creatorcontrib>Negre, Elsa</creatorcontrib><title>Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining</title><description>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.</description><subject>Computer Science - Information Retrieval</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj8lOwzAUAH3hgAofwAn_QMLzFsfHKmITRZWgnCPHS2optSMnLOXrCYXTXEYjDUJXBEpeCwE3On-Fj5JyICUwKeEcvb04k_oYvkPs8Ws4hEFn3OQwuQnP-5ze-_1Ch9fjOASj55AiTh5v45yG1B-LTk_O4qeYPgdne4efQ1xKF-jM62Fyl_9cod3d7a55KDbb-8dmvSl0JaEQxLCaiU5RT2XFhQUJ1BJFpVXeK2kdcK2oAL9I3BDpQBrFK6JVDbKjbIWu_7Knr3bM4aDzsf39a09_7Af10Eqk</recordid><startdate>20240108</startdate><enddate>20240108</enddate><creator>Le, Ngoc Luyen</creator><creator>Abel, Marie-Hélène</creator><creator>Negre, Elsa</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20240108</creationdate><title>Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining</title><author>Le, Ngoc Luyen ; Abel, Marie-Hélène ; Negre, Elsa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a670-51c3835b92f27645d0702d1927d9ff97de04a9250f35b4c17e07c9461a9807b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computer Science - Information Retrieval</topic><toplevel>online_resources</toplevel><creatorcontrib>Le, Ngoc Luyen</creatorcontrib><creatorcontrib>Abel, Marie-Hélène</creatorcontrib><creatorcontrib>Negre, Elsa</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Le, Ngoc Luyen</au><au>Abel, Marie-Hélène</au><au>Negre, Elsa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining</atitle><date>2024-01-08</date><risdate>2024</risdate><abstract>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.</abstract><doi>10.48550/arxiv.2401.03770</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Information Retrieval |
| title | Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining |
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