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Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision

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]

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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 08:55
Last Modified:15 Jun 2011 10:07

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