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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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
|Deposited By:||Professor Philip Morrow|
|Deposited On:||04 May 2010 09:55|
|Last Modified:||15 Jun 2011 11:07|
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