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Intelligent Data Engineering and Automated Learning – IDEAL 2006

Volume 4224 of the series Lecture Notes in Computer Science pp 961-969

Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision

  • Xin HongAffiliated withSchool of Computing and Information Engineering, University of Ulster
  • , Sally McCleanAffiliated withSchool of Computing and Information Engineering, University of Ulster
  • , Bryan ScotneyAffiliated withSchool of Computing and Information Engineering, University of Ulster
  • , Philip MorrowAffiliated withSchool of Computing and Information Engineering, University of Ulster

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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.