{"title":"Context-Based Disaster Management Support","authors":"A. Smirnov, M. Pashkin, N. Chilov, T. Levashova","doi":"10.1109/DIS.2006.19","DOIUrl":null,"url":null,"abstract":"The paper describes an approach to decision making support for disaster management. The approach is based on the methodology that assumes three levels of information integration. The application domain is described via an application ontology using the formalism of object-oriented constraint networks. The problem is described via an abstract context that is obtained as a result of the slicing operation on the application ontology. Finally, filling the abstract context with up-to-date information about the current situation produces an operational context. Contexts of both types share the same knowledge representation formalism that is used by the application ontology. As a result the operational context can be considered as a constraint satisfaction problem. Solving this task produces feasible decisions in the current situation","PeriodicalId":318812,"journal":{"name":"IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS'06)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DIS.2006.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The paper describes an approach to decision making support for disaster management. The approach is based on the methodology that assumes three levels of information integration. The application domain is described via an application ontology using the formalism of object-oriented constraint networks. The problem is described via an abstract context that is obtained as a result of the slicing operation on the application ontology. Finally, filling the abstract context with up-to-date information about the current situation produces an operational context. Contexts of both types share the same knowledge representation formalism that is used by the application ontology. As a result the operational context can be considered as a constraint satisfaction problem. Solving this task produces feasible decisions in the current situation