Case-based Reasoning for Crisis Response: Case Representation and Case Retrieval

Abstract With the multiple occurrences of natural and man-made disasters, supporting emergency decision makers (EDMs) in crisis response is primordial. Case-based reasoning (CBR) is a fitting problem-solving paradigm to solve crisis response issues. The performance of the CBR method depends on the steps of case representation and case retrieval. This paper firstly proposes the use of an ontology in order to represent crisis response cases. Then, it develops a two-stage case retrieval method. This latter firstly matches crisis events in order to generate a set of potential similar cases and then matches crisis impacts to obtain a set of the most similar cases. In addition, the proposed case retrieval method integrates cumulative prospect theory (CPT) in similarity measurement for the purpose of taking into account the psychological behavior of the EDM in the process of case retrieval. Finally, a case study using flood crisis real cases is used to illustrate our proposed method.

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