Evidential integration of semantically heterogeneous aggregates in distributed databases with imprecision

Authors:
Xin Hong;Sally McClean;Bryan Scotney;Philip Morrow
Affiliations:
School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland, UK;School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland, UK;School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland, UK;School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland, UK
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

Citing 4
Cited 0

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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.