Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision

  • Xin Hong
  • Sally McClean
  • Bryan Scotney
  • Philip Morrow
Conference paper

DOI: 10.1007/11875581_115

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)
Cite this paper as:
Hong X., McClean S., Scotney B., Morrow P. (2006) Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision. In: Corchado E., Yin H., Botti V., Fyfe C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xin Hong
    • 1
  • Sally McClean
    • 1
  • Bryan Scotney
    • 1
  • Philip Morrow
    • 1
  1. 1.School of Computing and Information EngineeringUniversity of UlsterColeraine, Northern IrelandUK

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