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GSMA: A Structural Matching Algorithm for Schema Matching in Data Warehousing

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3614))

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Abstract

Schema matching, the problem of finding semantic correspondences between elements of source and warehouse schemas, plays a key role in data warehousing. Currently, schema mapping is largely determined manually by domain experts, thus a labor-intensive process. In this paper, we propose a structural matching algorithm based on semantic similarity propagation. Experimental results on several real-world domains are presented, and show that the algorithm discovers semantic mappings with a high degree of accuracy.

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References

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Author information

Authors and Affiliations

  1. Institute of Software, Chinese Academy of Sciences, Beijing, 100080, P.R. China

    Wei Cheng & Yufang Sun

Authors
  1. Wei Cheng
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  2. Yufang Sun
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Cheng, W., Sun, Y. (2005). GSMA: A Structural Matching Algorithm for Schema Matching in Data Warehousing. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_50

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  • DOI: https://doi.org/10.1007/11540007_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28331-7

  • Online ISBN: 978-3-540-31828-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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