@article{Amailef2013,
	title = {Ontology-supported case-based reasoning approach for intelligent m-{Government} emergency response services},
	volume = {55},
	issn = {01679236},
	url = {http://www.sciencedirect.com/science/article/pii/S0167923613000043},
	doi = {10.1016/j.dss.2012.12.034},
	abstract = {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.},
	number = {1},
	urldate = {2016-01-07},
	journal = {Decision Support Systems},
	author = {Amailef, Khaled and Lu, Jie},
	month = apr,
	year = {2013},
	pages = {79--97},
}

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