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

Ngoc Luyen Le , Marie-Hélène Abel (1) , Elsa Negre

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

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.

Keywords: Crisis Management; Knowledge Representation; Ontology; Semantic Similarity

Domains: Computer Science [cs]

Ngoc Luyen Le, Marie-Hélène Abel, Elsa Negre. Recognizing Similar Crises through the Application of Ontology-based Knowledge Mining. 57th Hawaii International Conference on System Sciences, Jan 2024, Hawaii, United States. ⟨hal-04378722⟩