Efficiently computing iceberg cubes with complex constraints through bounding

Chou, P and Zhang, X 2003, 'Efficiently computing iceberg cubes with complex constraints through bounding', in Advances in Knowledge Discovery and Data Mining, Seoul, 1 January 2003.


Document type: Conference Paper
Collection: Conference Papers

Title Efficiently computing iceberg cubes with complex constraints through bounding
Author(s) Chou, P
Zhang, X
Year 2003
Conference name Pacific-Asia Conference on Knowledge Discovery and Data Mining
Conference location Seoul
Conference dates 1 January 2003
Proceedings title Advances in Knowledge Discovery and Data Mining
Publisher Springer
Place of publication Berlin
Abstract AData cubes facilitate fast On-Line Analytical Processing (OLAP). Iceberg cubes are special cubes comprise only the multidimensional groups satisfying some user-specified constraints. Previous algorithms have focused on iceberg cubes defined by relatively simple constraints such as “COUNT(*) ≥ δ” and “COUNT(*) ≥ δ AND AV G(Profit) ≥ α”. We propose an algorithm I-Cubing that computes iceberg cubes defined by complex constraints involving multiple predicates of aggregates such as “COUNT(*) ≥ δ AND (AV G(Profit) ≥ α OR AV G(profit) ≤ β)”. State-of-the-art iceberg cubing algorithms: BUC cannot handle such cases whereas H-Cubing has to incur extra cost. Our proposed bounding technique can prune for all the given constraints at once without extra cost. Experiments show that bounding has superior pruning power and I-Cubing is twice as fast as H-Cubing. Furthermore, I-Cubing performs equally well with more complex constraints.
Subjects Data Format not elsewhere classified
DOI - identifier 10.1007/3-540-36175-8_42
Copyright notice © Springer-Verlag Berlin Heidelberg 2003
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