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International Conference on Database Systems for Advanced Applications

DASFAA 2010: Database Systems for Advanced Applications pp 422–433Cite as

GRAMS3: An Efficient Framework for XML Structural Similarity Search

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6193))

Abstract

Structural similarity search is a fundamental technology for XML data management. However, existing methods do not scale well with large volume of XML document. The pq-gram is an efficient way of extracting substructure from the tree-structured data for approximate structural similarity search. In this paper, we propose an effective framework GRAMS3 for evaluating structural similarity of XML data. First pq-grams of XML document are extracted; then we study the characteristics of pq-gram of XML and generate doc-gram vector using TGF-IGF model for XML tree; finally we employ locality sensitive hashing for efficiently structural similarity search of XML documents. An empirical study using both synthetic and real datasets demonstrates the framework is efficient.

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Author information

Authors and Affiliations

  1. School of Computer Science, Fudan University, Shanghai, 200433, P.R. China

    Peisen Yuan, Chaofeng Sha & Ming Gao

  2. Shanghai Key Laboratory of Intelligent Information Processing, Shanghai, 200433, P.R. China

    Peisen Yuan, Chaofeng Sha, Ming Gao & Aoying Zhou

  3. Shanghai Key Laboratory of Trustworthy Computing, Software Engineering Institute, East China Normal University, Shanghai, 200062, P.R. China

    Xiaoling Wang & Aoying Zhou

Authors
  1. Peisen Yuan
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  2. Xiaoling Wang
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  3. Chaofeng Sha
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  4. Ming Gao
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  5. Aoying Zhou
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Editor information

Editors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo, 606-8501, Kyoto, Japan

    Masatoshi Yoshikawa

  2. Information School, Renmin University of China, 100872, Beijing, China

    Xiaofeng Meng

  3. Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji, 671-2280, Hyogo, Japan

    Takayuki Yumoto

  4. Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Sakyo, 606-8501, Kyoto, Japan

    Qiang Ma

  5. Institute of HCI and Media Integration, Tsinghua University, 100084, Bejing, China

    Lifeng Sun

  6. Department of Information Science, Ochanomizu University, 2-1-1, Otsuka, Bunkyo-ku, 112-8610, Tokyo, Japan

    Chiemi Watanabe

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Yuan, P., Wang, X., Sha, C., Gao, M., Zhou, A. (2010). GRAMS3: An Efficient Framework for XML Structural Similarity Search. In: Yoshikawa, M., Meng, X., Yumoto, T., Ma, Q., Sun, L., Watanabe, C. (eds) Database Systems for Advanced Applications. DASFAA 2010. Lecture Notes in Computer Science, vol 6193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14589-6_43

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  • DOI: https://doi.org/10.1007/978-3-642-14589-6_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14588-9

  • Online ISBN: 978-3-642-14589-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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