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An Adaptive Approach of Approximate Substring Matching

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Database Systems for Advanced Applications (DASFAA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9642))

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Abstract

Approximate substring matching is a common problem in many applications. In this paper, we study approximate substring matching with edit distance constraints. Existing methods are very sensitive to query strings or query parameters like query length and edit distance. To address the problem, we propose a new approach using partition scheme. It first partitions a query into several segments, and finds matching substrings of these segments as candidates, then performs a bidirectional verification on these candidates to get final results. We devise an even partition scheme to efficiently find candidates, and a best partition scheme to find high quality candidates. Furthermore, through theoretical analysis, we find that the best partition scheme cannot always outperform the even partition scheme. Thus we propose an adaptive approach for selectively choosing scheme using statistic knowledge. We conduct comprehensive experiments to demonstrate the efficiency and quality of our proposed method.

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Notes

  1. 1.

    https://genome.ucsc.edu/.

  2. 2.

    http://www.uniprot.org/.

  3. 3.

    https://www.gutenberg.org/.

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Acknowledgements

The work was partially supported by the NSF of China for Outstanding Young Scholars under grant 61322208, the NSF of China under grants 61272178, 61572122, the NSF of China for Key Program under grant 61532021, and ARC DP140103499.

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Liaoning, 110819, China

    Jiaying Wang, Xiaochun Yang & Bin Wang

  2. Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne, VIC, 3122, Australia

    Chengfei Liu

Authors
  1. Jiaying Wang
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  2. Xiaochun Yang
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  3. Bin Wang
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  4. Chengfei Liu
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Corresponding author

Correspondence to Xiaochun Yang .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology, Atlanta, Georgia, USA

    Shamkant B. Navathe

  2. University of Texas at Dallas, Richardson, Texas, USA

    Weili Wu

  3. University of Minnesota, Minneapolis, Minnesota, USA

    Shashi Shekhar

  4. Renmin University, Beijing, China

    Xiaoyong Du

  5. Fudan University, Shanghai, China

    X. Sean Wang

  6. Rutgers, The State University of New Jer, New Brunswick, New Jersey, USA

    Hui Xiong

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Wang, J., Yang, X., Wang, B., Liu, C. (2016). An Adaptive Approach of Approximate Substring Matching. In: Navathe, S., Wu, W., Shekhar, S., Du, X., Wang, X., Xiong, H. (eds) Database Systems for Advanced Applications. DASFAA 2016. Lecture Notes in Computer Science(), vol 9642. Springer, Cham. https://doi.org/10.1007/978-3-319-32025-0_31

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  • DOI: https://doi.org/10.1007/978-3-319-32025-0_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32024-3

  • Online ISBN: 978-3-319-32025-0

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