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Pacific-Asia Conference on Knowledge Discovery and Data Mining

PAKDD 2006: Advances in Knowledge Discovery and Data Mining pp 673–678Cite as

Enhanced DB-Subdue: Supporting Subtle Aspects of Graph Mining Using a Relational Approach

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3918))

Abstract

This paper addresses subtle aspects of graph mining using an SQL-based approach. The enhancements addressed in this paper include detection of cycles, effect of overlapping substructures on compression, and development of a minimum description length for the relational approach. Extensive performance evaluation has been conducted to evaluate the extensions.

This work was supported, in part, by NSF (grants IIS-0097517, IIS-0326505, and EIA-0216500).

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References

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Author information

Authors and Affiliations

  1. The University of Texas at Arlington, Arlington, TX, 76019, USA

    Ramanathan Balachandran, Srihari Padmanabhan & Sharma Chakravarthy

Authors
  1. Ramanathan Balachandran
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  2. Srihari Padmanabhan
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  3. Sharma Chakravarthy
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Editor information

Editors and Affiliations

  1. Nanyang Technological University, Singapore

    Wee-Keong Ng

  2. Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan

    Masaru Kitsuregawa

  3. School of Computer Science and Technology, Heilongjiang University, China

    Jianzhong Li

  4. School of Computer Engineering, Nanyang Technological University, 639798, Singapore, Singapore

    Kuiyu Chang

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Balachandran, R., Padmanabhan, S., Chakravarthy, S. (2006). Enhanced DB-Subdue: Supporting Subtle Aspects of Graph Mining Using a Relational Approach. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_77

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  • DOI: https://doi.org/10.1007/11731139_77

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33206-0

  • Online ISBN: 978-3-540-33207-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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