Evidential integration of semantically heterogeneous aggregates in distributed databases with imprecision

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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. © Springer-Verlag Berlin Heidelberg 2006.

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Xin, H., McClean, S., Scotney, B., & Morrow, P. (2006). Evidential integration of semantically heterogeneous aggregates in distributed databases with imprecision. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4224 LNCS, pp. 961–969). Springer Verlag. https://doi.org/10.1007/11875581_115

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