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Social and Behavioral Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

2007

Kno.e.sis Publications

Data Mining

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Full-Text Articles in Social and Behavioral Sciences

Efficient Computation Of Iceberg Cubes By Bounding Aggregate Functions, Xiuzhen Zhang, Pauline Lienhua Chou, Guozhu Dong Jul 2007

Efficient Computation Of Iceberg Cubes By Bounding Aggregate Functions, Xiuzhen Zhang, Pauline Lienhua Chou, Guozhu Dong

Kno.e.sis Publications

The iceberg cubing problem is to compute the multidimensional group-by partitions that satisfy given aggregation constraints. Pruning unproductive computation for iceberg cubing when nonantimonotone constraints are present is a great challenge because the aggregate functions do not increase or decrease monotonically along the subset relationship between partitions. In this paper, we propose a novel bound prune cubing (BP-Cubing) approach for iceberg cubing with nonantimonotone aggregation constraints. Given a cube over n dimensions, an aggregate for any group-by partition can be computed from aggregates for the most specific n--dimensional partitions (MSPs). The largest and smallest aggregate values computed this way become …