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Approximate Aggregate Queries with Guaranteed Error Bounds

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

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Abstract

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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References

  1. N. Beckmann, H. Kriegel, R. Schneider, and B. Seeger: The R*-tree: an efficient and robust access method for points and rectangles. Proc. of ACM SIGMOD Conference (1990) 322–331

    Google Scholar 

  2. Seok-Ju Chun, Chin-Wan Chung, Ju-Hong Lee, and Seok-Lyong Lee: Dynamic Update Cube for Range-Sum Queries. Proc. of VLDB Conference (2001) 521–530

    Google Scholar 

  3. C. Ho, R. Agrawal, N. Megido, R. Srikant: Range queries in OLAP Data Cubes. Proc. of ACM SIGMOD Conference (1997) 73–88

    Google Scholar 

  4. L. Lazaridis, and S. Mehrotra: Progressive Approximate Aggregate Queries with a Multi-Resolution Tree Structure. Proc. of ACM SIGMOD Conference (2001) 401–412

    Google Scholar 

  5. M. Riedewald, D. Agrawal, and A. E. Abbadi: pCube: Update-Efficient Online Aggregation with Progressive Feedback and Error Bounds. Proc. of SSDBM Conference (2000) 95–108

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Internet Information, Ansan College, 752, Il-Dong, SangRok-Ku, Ansan, Korea

    Seok-Ju Chun

  2. School of Computer Science and Engineering, Inha University, 253, YongHyun-dong, Nam-Ku, Inchon, Korea

    Ju-Hong Lee

  3. School of Industrial and Information System Engineering, Hankuk University of Foreign Studies, Yongin-si, Kyounggi-do, Korea

    Seok-Lyong Lee

Authors
  1. Seok-Ju Chun
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  2. Ju-Hong Lee
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  3. Seok-Lyong Lee
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Guoyin Wang

  2. Department of Computer Science, Nanchang University, Nanchang, 330029, P.R. China

    Qing Liu

  3. Department of Computer Science, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Yiyu Yao

  4. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2003 Springer-Verlag Berlin Heidelberg

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Chun, SJ., Lee, JH., Lee, SL. (2003). Approximate Aggregate Queries with Guaranteed Error Bounds. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_104

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

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

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