Skip to main content

pq-Hash: An Efficient Method for Approximate XML Joins

  • Conference paper
Web-Age Information Management (WAIM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6185))

Included in the following conference series:

Abstract

Approximate matching between large tree sets is broadly used in many applications such as data integration and XML de-duplication. However, most existing methods suffer for low efficiency, thus do not scale to large tree sets.

pq-gram is a widely-used method with high quality of matches. In this paper, we propose pq-hash as an improvement to pq-gram. As the base of pq-hash, a randomized data structure, pq-array, is developed. With pq-array, large trees are represented as small fixed sized arrays. Sort-merge and hash join technique is applied based on these pq-arrays to avoid nested-loop join. From theoretical analysis and experimental results, retaining high join quality, pq-hash gains much higher efficiency than pq-gram.

Supported by the National Science Foundation of China (No 60703012, 60773063), the NSFC-RGC of China(No. 60831160525), National Grant of Fundamental Research 973 Program of China (No.2006CB303000), National Grant of High Technology 863 Program of China (No. 2009AA01Z149), Key Program of the National Natural Science Foundation of China (No. 60933001), National Postdoctor Foundtaion of China (No. 20090450126), Development Program for Outstanding Young Teachers in Harbin Institute of Technology (no. HITQNJS.2009.052.).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Augsten, N., Böhlen, M.H., Dyreson, C.E., Gamper, J.: Approximate joins for data-centric XML. In: ICDE, pp. 814–823 (2008)

    Google Scholar 

  2. Augsten, N., Böhlen, M.H., Gamper, J.: Approximate matching of hierarchical data using pq-grams. In: VLDB, pp. 301–312 (2005)

    Google Scholar 

  3. Augsten, N., Böhlen, M.H., Gamper, J.: An incrementally maintainable index for approximate lookups in hierarchical data. In: VLDB, pp. 247–258 (2006)

    Google Scholar 

  4. Bille, P.: A survey on tree edit distance and related problems. Theor. Comput. Sci. 337(1-3), 217–239 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  5. Broder, A.Z., Charikar, M., Frieze, A.M., Mitzenmacher, M.: Min-wise independent permutations (extended abstract). In: STOC, pp. 327–336 (1998)

    Google Scholar 

  6. Cobena, G., Abiteboul, S., Marian, A.: Detecting changes in XML documents. In: ICDE, pp. 41–52 (2002)

    Google Scholar 

  7. Cohen, E., Datar, M., Fujiwara, S., Gionis, A., Indyk, P., Motwani, R., Ullman, J.D., Yang, C.: Finding interesting associations without support pruning. IEEE Trans. Knowl. Data Eng. 13(1), 64–78 (2001)

    Article  Google Scholar 

  8. Demaine, E.D., Mozes, S., Rossman, B., Weimann, O.: An optimal decomposition algorithm for tree edit distance. In: Arge, L., Cachin, C., Jurdziński, T., Tarlecki, A. (eds.) ICALP 2007. LNCS, vol. 4596, pp. 146–157. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Gionis, A., Indyk, P., Motwani, R.: Similarity search in high dimensions via hashing. In: VLDB, pp. 518–529 (1999)

    Google Scholar 

  10. Haveliwala, T.H., Gionis, A., Indyk, P.: Scalable techniques for clustering the web. In: WebDB (Informal Proceedings), pp. 129–134 (2000)

    Google Scholar 

  11. Karp, R.M., Rabin, M.O.: Efficient randomized pattern-matching algorithms. IBM Journal of Research and Development 31(2), 249–260 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  12. Klein, P.N.: Computing the edit-distance between unrooted ordered trees. In: Bilardi, G., Pietracaprina, A., Italiano, G.F., Pucci, G. (eds.) ESA 1998. LNCS, vol. 1461, pp. 91–102. Springer, Heidelberg (1998)

    Google Scholar 

  13. Lee, K.-H., Choy, Y.-C., Cho, S.-B.: An efficient algorithm to compute differences between structured documents. IEEE Trans. Knowl. Data Eng. 16(8), 965–979 (2004)

    Article  Google Scholar 

  14. Metwally, A., Agrawal, D., Abbadi, A.E.: Detectives: detecting coalition hit inflation attacks in advertising networks streams. In: WWW, pp. 241–250 (2007)

    Google Scholar 

  15. Tai, K.-C.: The tree-to-tree correction problem. J. ACM 26(3), 422–433 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  16. Zhang, K., Shasha, D.: Simple fast algorithms for the editing distance between trees and related problems. SIAM J. Comput. 18(6), 1245–1262 (1989)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, F., Wang, H., Hao, L., Li, J., Gao, H. (2010). pq-Hash: An Efficient Method for Approximate XML Joins. In: Shen, H.T., et al. Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16720-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16720-1_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16719-5

  • Online ISBN: 978-3-642-16720-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics