Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services

Amailef, K; Lu, J

Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services

Amailef, K Lu, J

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Publication Type:: Journal Article
Citation:: Decision Support Systems, 2013, 55 (1), pp. 79 - 97
Issue Date:: 2013-04-01

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Field	Value	Language
dc.contributor.author	Amailef, K	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.issued	2013-04-01	en_US
dc.identifier.citation	Decision Support Systems, 2013, 55 (1), pp. 79 - 97	en_US
dc.identifier.issn	0167-9236	en_US
dc.identifier.uri	http://hdl.handle.net/10453/23742
dc.description.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. Copyright © 2013 Published by Elsevier B.V. All rights reserved.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0880739
dc.relation.ispartof	Decision Support Systems	en_US
dc.relation.isbasedon	10.1016/j.dss.2012.12.034	en_US
dc.subject.classification	Information Systems	en_US
dc.title	Ontology-supported case-based reasoning approach for intelligent m-Government emergency response services	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	55	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	15 Commerce, Management, Tourism and Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	55	en_US

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. Copyright © 2013 Published by Elsevier B.V. All rights reserved.

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http://hdl.handle.net/10453/23742