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Flow Graphs and Decision Algorithms Read chapter Read first chapter

2003 | OriginalPaper | Chapter

Approximate Aggregate Queries with Guaranteed Error Bounds

Authors : Seok-Ju Chun, Ju-Hong Lee, Seok-Lyong Lee

Published in: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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It is very important to provide analysts with guaranteed error bounds for approximate aggregate queries in many current enterprise applications such as the decision support systems. In this paper, we propose a general technique to provide tight error bounds for approximate results to OLAP range-sum queries. We perform an extensive experiment on diverse data sets, and examine the effectiveness of our proposed method with respect to various dimensions of the data cube and query sizes.

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Metadata
Title
Approximate Aggregate Queries with Guaranteed Error Bounds
Authors
Seok-Ju Chun
Ju-Hong Lee
Seok-Lyong Lee
Copyright Year
2003
Publisher
Springer Berlin Heidelberg
Book
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Print ISBN: 978-3-540-14040-5

Electronic ISBN: 978-3-540-39205-7

Copyright Year: 2003

DOI
https://doi.org/10.1007/3-540-39205-X_104