Skip to main content
SpringerLink
Log in
Book cover

Transactions on Large-Scale Data- and Knowledge-Centered Systems X pp 34–59Cite as

Computing Skyline Incrementally in Response to Online Preference Modification

  • Chapter

Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 8220))

Abstract

Skyline queries retrieve the most interesting objects from a database with respect to multi-dimensional preferences. Identifying and extracting the relevant data corresponding to multiple criteria provided by users remains a difficult task, especially when the dataset is large. EC 2 Sky, our proposal, focuses on how to answer efficiently skyline queries in the presence of dynamic user preferences and despite large volumes of data. In 2008-2009, Wong et al. showed that the skyline associated with any preference on a particular dimension can be computed, without domination tests, from the skyline points associated with first order preferences on that same dimension. Consequently, they propose to materialize skyline points associated with the most preferred values in a specific data structure called IPO-tree (Implicit Preference Order Tree). However, the size of the IPO-tree is exponential with respect to the number of dimensions. While reusing the merging property proposed by Wong et al. to deal with the refinements of preferences on a single dimension, we propose an incremental method for calculating the skyline points related to several dimensions associated with dynamic preferences. For this purpose, a materialization of linear size which allows a great flexibility for dimension preference updates is defined. This contribution improves notably the execution time and storage size of queries. Experiments on synthetic data highlight the relevance of EC 2 Sky compared to IPO-Tree.

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

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Balke, W.T., Guntzer, U., Siberski, W.: Exploiting indifference for customization of partial order skylines. In: Proceedings of the 10th International Database Engineering and Applications Symposium, pp. 80–88. IEEE Computer Society (2006)

    Google Scholar 

  2. Bentley, J.L., Kung, H.T., Schkolnick, M., Thompson, C.D.: On the average number of maxima in a set of vectors and applications. J. ACM 25(4), 536–543 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bitran, G.R., Magnanti, T.L.: The structure of admissible points with respect to cone dominance. Optimization Theory and Applications 29(4), 573–614 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  4. Borzsonyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proc. of the 17th International Conference on Data Engineering, pp. 421–430. IEEE Computer Society (2001)

    Google Scholar 

  5. Bouadi, T., Cordier, M.-O., Quiniou, R.: Incremental computation of skyline queries with dynamic preferences. In: Liddle, S.W., Schewe, K.-D., Tjoa, A.M., Zhou, X. (eds.) DEXA 2012, Part I. LNCS, vol. 7446, pp. 219–233. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  6. Brando, C., Goncalves, M., González, V.: Evaluating top-k skyline queries over relational databases. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA 2007. LNCS, vol. 4653, pp. 254–263. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  7. Chen, L., Lian, X.: Efficient processing of metric skyline queries. IEEE Trans. on Knowl. and Data Eng. 21(3), 351–365 (2009)

    Article  Google Scholar 

  8. Chomicki, J., Godfrey, P., Gryz, J., Liang, D.: Skyline with presorting: Theory and optimizations. In: Proc. of Intelligent Information Systems, pp. 595–604. Springer, Heidelberg (2005)

    Google Scholar 

  9. Godfrey, P., Shipley, R., Gryz, J.: Algorithms and analyses for maximal vector computation. The VLDB Journal 16(1), 5–28 (2007)

    Article  Google Scholar 

  10. Huang, Z., Guo, J., Sun, S.L., Wang, W.: Efficient optimization of multiple subspace skyline queries. J. Comput. Sci. Technol. 23(1), 103–111 (2008)

    Article  MathSciNet  Google Scholar 

  11. Jin, W., Tung, A.K.H., Ester, M., Han, J.: On efficient processing of subspace skyline queries on high dimensional data. In: Proc. of the 19th International Conference on Scientific and Statistical Database Management. IEEE Computer Society (2007)

    Google Scholar 

  12. Mindolin, D., Chomicki, J.: Preference elicitation in prioritized skyline queries. The VLDB Journal 20(2), 157–182 (2011)

    Article  Google Scholar 

  13. Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. ACM Trans. Database Syst. 30(1), 41–82 (2005)

    Article  Google Scholar 

  14. Pei, J., Jin, W., Ester, M., Tao, Y.: Catching the best views of skyline: a semantic approach based on decisive subspaces. In: Proc of the 31st International Conference on Very Large Data Bases, pp. 253–264, VLDB Endowment (2005)

    Google Scholar 

  15. Raïssi, C., Pei, J., Kister, T.: Computing closed skycubes. Proc. VLDB Endow. 3(1), 838–847 (2010)

    Google Scholar 

  16. Sawaragi, Y., Nakayama, H., Tanino, T.: Theory of Multiobjective Optimization. Academic Press, Orlando (1985)

    MATH  Google Scholar 

  17. Tan, K.L., Eng, P.K., Ooi, B.C.: Efficient progressive skyline computation. In: Proceedings of the 27th International Conference on Very Large Data Bases, pp. 301–310. Morgan Kaufmann Publishers Inc. (2001)

    Google Scholar 

  18. Tao, Y., Xiao, X., Pei, J.: Efficient skyline and top-k retrieval in subspaces. IEEE Trans. on Knowl. and Data Eng. 19(8), 1072–1088 (2008)

    Article  Google Scholar 

  19. Trenkler, G.: In: Johnson, N.l., Kotz, S., kemp, A.W. (eds.) Univariate Discrete Distributions, 2nd edn. John wiley (1994) ISBN 0-471-54897-9; Computational Statistics & Data Analysis, 17(2), 240–241 (1994)

    Google Scholar 

  20. Wong, R.C.W., Fu, A.W.C., Pei, J., Ho, Y.S., Wong, T., Liu, Y.: Efficient skyline querying with variable user preferences on nominal attributes. Proc. VLDB Endow. 1(1), 1032–1043 (2008)

    Google Scholar 

  21. Wong, R.C.W., Pei, J., Fu, A.W.C., Wang, K.: An erratum on “online skyline analysis with dynamic preferences on nominal attributes”. IEEE Trans. on Knowl. and Data Eng. (to be published)

    Google Scholar 

  22. Wong, R.C.W., Pei, J., Fu, A.W.C., Wang, K.: Online skyline analysis with dynamic preferences on nominal attributes. IEEE Trans. on Knowl. and Data Eng. 21(1), 35–49 (2009)

    Article  Google Scholar 

  23. Xia, T., Zhang, D., Tao, Y.: On skylining with flexible dominance relation. In: Proc. of the 2008 IEEE 24th International Conference on Data Engineering, pp. 1397–1399. IEEE Computer Society (2008)

    Google Scholar 

  24. Yuan, Y., Lin, X., Liu, Q., Wang, W., Yu, J.X., Zhang, Q.: Efficient computation of the skyline cube. In: Proc. of the 31st International Conference on Very Large Data Bases, pp. 241–252, VLDB Endowment (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. IRISA - University of Rennes 1, France

    Tassadit Bouadi & Marie-Odile Cordier

  2. IRISA - INRIA Rennes, Campus de Beaulieu, 35042, Rennes, France

    René Quiniou

Authors
  1. Tassadit Bouadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marie-Odile Cordier
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. René Quiniou
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, 118 route de Narbonne, 31062, Toulouse Cedex, France

    Abdelkader Hameurlain

  2. FAW, University of Linz, Altenbergerstraße 69, 4040, Linz, Austria

    Josef Küng  & Roland Wagner  & 

  3. Brigham Young University, 84602, Provo, UT, USA

    Stephen W. Liddle

  4. Software Competence Centre Hagenberg, 4232, Hagenberg, Austria

    Klaus-Dieter Schewe

  5. The Universtiy of Queensland, 4072, Brisbane, QLD, Australia

    Xiaofang Zhou

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bouadi, T., Cordier, MO., Quiniou, R. (2013). Computing Skyline Incrementally in Response to Online Preference Modification. In: Hameurlain, A., Küng, J., Wagner, R., Liddle, S.W., Schewe, KD., Zhou, X. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems X. Lecture Notes in Computer Science, vol 8220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41221-9_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-41221-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41220-2

  • Online ISBN: 978-3-642-41221-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation