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Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Hong, Xin, McClean, S, Scotney, Bryan and Morrow, PJ (2006) Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision. In: Intelligent Data Engineering and Automated Learning – IDEAL 2006. Springer, pp. 961-969. ISBN 978-3-540-45485-4 [Book section]

Full text not available from this repository.

URL: http://www.springerlink.com/content/g5m1p8083312752w/

DOI: doi:10.1007/11875581_115

Abstract

The mass function of evidential theory provides a means of representing ignorance in lack of information. In this paper we propose mass function models of aggregate views held as summary tables in a distributed database. This model particularly suits statistical databases in which the data usually presents imprecision, including missing values and overlapped categories of aggregate classification. A new aggregation combination operator is developed to accomplish the integration of semantically heterogeneous aggregate views in such distributed databases.

Item Type:Book section
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:8935
Deposited By:Professor Philip Morrow
Deposited On:04 May 2010 09:55
Last Modified:15 Jun 2011 11:07

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