Reduced representations of Emerging Cubes for OLAP database mining
by Sebastien Nedjar, Alain Casali, Rosine Cicchetti, Lotfi Lakhal
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 4, No. 3/4, 2009

Abstract: In this paper, we investigate reduced representations for the Emerging Cube. We use the borders, classical in data mining, for the Emerging Cube. These borders can support classification tasks to know whether a trend is emerging or not. However, the borders do not make possible to retrieve the measure values. This is why we introduce two new and reduced representations without measure loss: the L-Emerging Closed Cube and Emerging Quotient Cube. We state the relationship between the introduced representations. Experiments performed on various data sets are intended to measure the size of the three reduced representations.

Online publication date: Tue, 03-Nov-2009

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