Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services
Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services
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DOI：
10.1016/j.dss.2012.12.034
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发表时间：
2013-04-01
影响因子：
7.5
通讯作者：
Lu, Jie
中科院分区：
文献类型：
--
作者：
Amailef, Khaled;Lu, Jie
迫切需要开发基于移动的应急响应系统（MERS），以帮助减少紧急情况下的风险。现有的系统只提供短消息服务（SMS）通知，并且决策支持很弱，特别是在人为灾害情况下。本文提出了一种MERS本体支持的案例推理（OS-CBR）方法，并实现，以支持应急决策者有效地应对突发事件。OS-CBR方法的优点在于它建立了一个案例检索过程，这为基于过去灾害事件的知识和解决方案的决策支持提供了一个更方便的系统。OS-CBR方法包括一组算法，已成功地实现了四个组成部分：数据采集;本体;知识库;和推理;作为MERS框架的子系统。一系列的实验和案例研究验证了OS-CBR方法和应用，并证明了其有效性。皇冠版权所有（c）2013由爱思唯尔B. V.出版保留所有权利。
There is a critical need to develop a mobile-based emergency response system (MERS) to help reduce risks in emergency situations. Existing systems only provide short message service (SMS) notifications, and the decision support is weak, especially in man-made disaster situations. This paper presents a MERS ontology-supported case-based reasoning (OS-CBR) method, with implementation, to support emergency decision makers to effectively respond to emergencies. The advantages of the OS-CBR approach is that it builds a case retrieving process, which provides a more convenient system for decision support based on knowledge from, and solutions provided for past disaster events. The OS-CBR approach includes a set of algorithms that have been successfully implemented in four components: data acquisition; ontology; knowledge base; and reasoning; as a sub-system of the MERS framework. A set of experiments and case studies validated the OS-CBR approach and application, and demonstrate its efficiency. Crown Copyright (c) 2013 Published by Elsevier B.V. All rights reserved.