Finding Top-K Correct XPath Queries of User’s Incorrect XPath Query

  • Kosetsu Ikeda
  • Nobutaka Suzuki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7446)

Abstract

Suppose that we have a DTD D and XML documents valid against D, and consider writing an XPath query to the documents. Unfortunately, a user often does not understand the entire structure of D exactly, especially in the case where D is very large and/or complex or D has been updated but the user misses it. In such cases, the user tends to write an incorrect XPath query q. However, it is difficult for the user to correct q by hand due to his/her lack of exact knowledge about the entire structure of D. In this paper, we propose an algorithm that finds, for an XPath query q, a DTD D, and a positive integer K, ”top-K” XPath queries ”most similar” to q among the XPath queries conforming to D so that a user select an appropriate query among the K queries. We also present some experimental studies.

Keywords

Short Path Problem Edit Operation XPath Query Location Step Simple Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Amer-Yahia, S., Cho, S., Srivastava, D.: Tree Pattern Relaxation. In: Jensen, C.S., Jeffery, K., Pokorný, J., Šaltenis, S., Bertino, E., Böhm, K., Jarke, M. (eds.) EDBT 2002. LNCS, vol. 2287, pp. 89–102. Springer, Heidelberg (2002)Google Scholar
  2. 2.
    Amer-Yahia, S., Lakshmanan, L.V., Pandit, S.: Flexpath: Flexible structure and full-text querying for xml. In: Proc. SIGMOD, pp. 83–94 (2004)Google Scholar
  3. 3.
    Choi, B.: What are real dtds like? In: Proc. WebDB, pp. 43–48 (2002)Google Scholar
  4. 4.
    Cohen, S., Brodianskiy, T.: Correcting queries for xml. Information Systems 34(8), 690–710 (2009)CrossRefGoogle Scholar
  5. 5.
    Eppstein, D.: Finding the k shortest paths. SIAM J. Computing 28(2), 652–673 (1998)MathSciNetMATHCrossRefGoogle Scholar
  6. 6.
    Fazzinga, B., Flesca, S., Furfaro, F.: Xpath query relaxation through rewriting rules. IEEE Transactions on Knowledge and Data Engineering 23, 1583–1600 (2011)CrossRefGoogle Scholar
  7. 7.
    Fazzinga, B., Flesca, S., Pugliese, A.: Retrieving xml data from heterogeneous sources through vague querying. ACM Trans. Internet Technol. 9(2), 7:1–7:35 (2009), http://doi.acm.org/10.1145/1516539.1516542 Google Scholar
  8. 8.
    Ives, Z.G., Halevy, A.Y., Weld, D.S.: An xml query engine for network-bound data. The VLDB Journal 11(4), 380–402 (2002)MATHCrossRefGoogle Scholar
  9. 9.
    Li, G., Feng, J., Wang, J., Zhou, L.: Effective keyword search for valuable lcas over xml documents. In: Proc. ACM CIKM, CIKM 2007, pp. 31–40. ACM (2007)Google Scholar
  10. 10.
    Li, Y., Yu, C., Jagadish, H.V.: Schema-free xquery. In: Proc. VLDB, pp. 72–83 (2004)Google Scholar
  11. 11.
    Li, Y., Yu, C., Jagadish, H.V.: Enabling schema-free xquery with meaningful query focus. The VLDB Journal 17, 355–377 (2008)CrossRefGoogle Scholar
  12. 12.
    Martins, E.: K-th shortest paths problem, http://www.mat.uc.pt/~eqvm/OPP/KSPP/KSPP.html
  13. 13.
    Marzal, A., Vidal, E.: Computation of normalized edit distance and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence 15, 926–932 (1993)CrossRefGoogle Scholar
  14. 14.
    Morishima, A., Kitagawa, H., Matsumoto, A.: A machine learning approach to rapid development of xml mapping queries. In: Proc. ICDE, pp. 276–287 (2004)Google Scholar
  15. 15.
    Schenkel, R., Theobald, M.: Feedback-Driven Structural Query Expansion for Ranked Retrieval of XML Data. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 331–348. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. 16.
    Schlieder, T.: Schema-Driven Evaluation of Approximate Tree-Pattern Queries. In: Jensen, C.S., Jeffery, K., Pokorný, J., Šaltenis, S., Bertino, E., Böhm, K., Jarke, M. (eds.) EDBT 2002. LNCS, vol. 2287, pp. 514–532. Springer, Heidelberg (2002), http://dl.acm.org/citation.cfm?id=645340.650204 CrossRefGoogle Scholar
  17. 17.
    Schmidt, A., Waas, F., Kersten, M., Carey, M., Manolescu, I., Busse, R.: Xmark: A benchmark for xml data managemet. In: Proc. VLDB, pp. 974–985 (2002)Google Scholar
  18. 18.
    Termehchy, A., Winslett, M.: Using structural information in xml keyword search effectively. ACM Trans. Database Syst. 36(1), 4 (2011)CrossRefGoogle Scholar
  19. 19.
    Xu, Y., Papakonstantinou, Y.: Efficient keyword search for smallest lcas in xml databases. In: Proc. ACM SIGMOD Conf., pp. 527–538. ACM (2005)Google Scholar
  20. 20.
    Wu, Y., Lele, N., Aroskar, R., Chinnusamy, S., Brenes, S.: Xqgen: an algebra-based xpath query generator for micro-benchmarking. In: Proc. CIKM, pp. 2109–2110 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kosetsu Ikeda
    • 1
  • Nobutaka Suzuki
    • 1
  1. 1.University of TsukubaTsukubaJapan

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