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Improving table compression with combinatorial optimization

Published in Symposium on Discrete Algorithms • Jan 6, 2002
NobleIDNI9P71W06R34S60
Authors:
Adam L. Buchsbaum
,
Glenn S. Fowler
,
Raffaele Giancarlo

Abstract

We study the problem of compressing massive tables within the partition-training paradigm introduced by Buchsbaum et al. [SODA'00], in which a table is partitioned by an off-line training procedure into disjoint intervals of columns, each of which is compressed separately by a standard, on-line comp...

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