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Relaxing Queries Based on XML Structure and Content Preferences

  • Wei Yan
  • Z. M. Ma
  • Fu Zhang
  • Xiangfu Meng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6724)

Abstract

In order to resolve the problem of the empty or many answers returned from XML, this paper proposes a contextual preference query method of XML structural relaxation and content scoring. To provide users with most relevant and ranked query results, firstly, we propose a XML contextual preference (XCP) model, where all the possible relaxing queries are determined by the user’s preferences. The XCP model allows users to express their interest on XML tree nodes, and then users assign interest scores to their interesting nodes for quickly providing best answers. Furthermore, based on the proposed XCP model, we propose a preference queries results ranking method, which includes: a Clusters_Merging algorithm to merge clusters based on the similarity of the context states, a Finding_Orders algorithm to find representative orders of the clusters, and a Top-k ranking algorithm to deal with the many answers problem. Results of preliminary user study demonstrate that our method can provide users with most relevant and ranked query results. The efficiency and effectiveness of the approach are also demonstrated by experimental results.

Keywords

XML structure and content query relaxation contextual preference Top-k ranking 

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References

  1. 1.
    Amer-Yahia, S., Cho, S., Srivastava, D.: Tree Pattern Relaxation. In: Proceedings of the EDBT Conference, pp. 496–513 (2002)Google Scholar
  2. 2.
    Amer-Yahia, S., Fundulaki, I., Lakshmanan, L.: Personalizing XML Search in Pimento. In: Proceedings of the ICDE Conference, pp. 906–915 (2007)Google Scholar
  3. 3.
    Amer-Yahia, S., Koudas, N., Marian, A., Srivastava, D., Toman, D.: Structure and Content Scoring for XML. In: Proceedings of the VLDB Conference, pp. 361–372 (2005)Google Scholar
  4. 4.
    Amer-Yahia, S., Lakshmanan, L., Pandit, S.: FleXPath: Flexible Structure and Full-Text Querying for XML. In: Proceedings of the SIGMOD Conference, pp. 83–94 (2004)Google Scholar
  5. 5.
    Agrawal, R., Rantzau, R., Terzi, E.: Context-sensitive Ranking. In: Proceedings of the SIGMOD Conference, pp. 383–394 (2006)Google Scholar
  6. 6.
    Cho, S., Balke, W.: Efficient Evaluation of Preference Query Processes Using Twig Caches. In: Proceedings of the RCIS Conference, pp. 365–374 (2009)Google Scholar
  7. 7.
    Cho, S., Balke, W.: Order-preserving Optimization of Twig Queries with Structural Preferences. In: Proceedings of the IDEAS Conference, pp. 219–229 (2008)Google Scholar
  8. 8.
    Cho, S., Balke, W.: Relaxing XML Preference Queries for Cooperative Retrieval. In: Proceedings of the ICEIS Conference, pp. 160–171 (2009)Google Scholar
  9. 9.
    Chomicki, J.: Preference Formulas in Relational Queries. ACM Trans. Database Syst. 28(4), 427–466 (2003)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Fagin, R., Lotem, A., Naor, M.: Optimal Aggregation Algorithms for Middleware. In: Proceedings of the PODS Conference, pp. 102–113 (2001)Google Scholar
  11. 11.
    Hristidis, V., Koudas, N., Papakonstantinou, Y.: Prefer: A System for the Efficient Execution of Multi-parametric Ranked Queries. In: Proceedings of the SIGMOD Conference, pp. 259–270 (2001)Google Scholar
  12. 12.
    Koutrika, G., Ioannidis, Y.: Constrained Optimalities in Query Personalization. In: Proceedings of the SIGMOD Conference, pp. 73–84 (2005)Google Scholar
  13. 13.
    Liu, X., Wan, C., Chen, L.: Effective XML Content and Structure Retrieval with Relevance Ranking. In: Proceedings of the CIKM Conference, pp. 147–156 (2009)Google Scholar
  14. 14.
    Marian, A., Amer-Yahia, S., Koudas, N.: Divesh Srivastava: Adaptive Processing of Top-K Queries in XML. In: Proceedings of the ICDE Conference, pp. 162–173 (2005)Google Scholar
  15. 15.
    Polyzotis, N., Garofalakis, M., Ioannidis, Y.: Approximate XML Query Answers. In: Proceedings of the SIGMOD Conference, pp. 263–274 (2004)Google Scholar
  16. 16.
    Stefanidis, K., Pitoura, E., Vassiliadis, P.: Adding Context to Preferences. In: Proceedings of the ICDE Conference, pp. 846–855 (2007)Google Scholar
  17. 17.
    Su, W., Wang, J., Huang, Q., Lochovsky, F.: Query Result Ranking over E-commerce Web Databases. In: Proceedings of the CIKM Conference, pp. 575–584 (2006)Google Scholar
  18. 18.
    Stefanidis, K., Pitoura, E.: Fast Contextual Preference Scoring of Database Tuples. In: Proceedings of the EDBT Conference, pp. 344–355 (2008)Google Scholar
  19. 19.
    Schlieder, T.: Similarity Search in XML Data Using Cost-Based Query Transformations. In: Proceedings of the WebDB Conference, pp. 19–24 (2001)Google Scholar
  20. 20.
    XMARK the XML-benchmark Project, http://monetdb.cwi.nl/xml/index.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Wei Yan
    • 1
  • Z. M. Ma
    • 1
  • Fu Zhang
    • 1
  • Xiangfu Meng
    • 2
  1. 1.College of Information Science and EngineeringNortheastern UniversityShenyangChina
  2. 2.College of Electronic and Information EngineeringLiaoning Technical UniversityHuludaoChina

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