Subspace Discovery for Promotion: A Cell Clustering Approach

  • Tianyi Wu
  • Jiawei Han
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5808)


The promotion analysis problem has been proposed in , where ranking-based promotion query processing techniques are studied to effectively and efficiently promote a given object, such as a product, by exploring ranked answers. To be more specific, in a multidimensional data set, our goal is to discover interesting subspaces in which the object is ranked high. In this paper, we extend the previously proposed promotion cube techniques and develop a cell clustering approach that is able to further achieve better tradeoff between offline materialization and online query processing. We formally formulate our problem and present a solution to it. Our empirical evaluation on both synthetic and real data sets show that the proposed technique can greatly speedup query processing with respect to baseline implementations.


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  1. 1.
    Arkin, E.M., Barequet, G., Mitchell, J.S.B.: Algorithms for two-box covering. In: Symposium on Computational Geometry, pp. 459–467 (2006)Google Scholar
  2. 2.
    Chang, K.C.-C., Hwang, S.-w.: Minimal probing: supporting expensive predicates for top-k queries. In: SIGMOD Conference, pp. 346–357 (2002)Google Scholar
  3. 3.
    Charikar, M., Panigrahy, R.: Clustering to minimize the sum of cluster diameters. In: STOC, pp. 1–10 (2001)Google Scholar
  4. 4.
    Doddi, S.R., Marathe, M.V., Ravi, S.S., Taylor, D.S., Widmayer, P.: Approximation algorithms for clustering to minimize the sum of diameters. In: Halldórsson, M.M. (ed.) SWAT 2000. LNCS, vol. 1851, pp. 237–250. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  5. 5.
    DuMouchel, W., Volinsky, C., Johnson, T., Cortes, C., Pregibon, D.: Squashing flat files flatter. In: KDD, pp. 6–15 (1999)Google Scholar
  6. 6.
    Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. J. Comput. Syst. Sci. 66(4), 614–656 (2003)MathSciNetCrossRefMATHGoogle Scholar
  7. 7.
    Han, J., Kamber, M.: Data mining: concepts and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2006)MATHGoogle Scholar
  8. 8.
    Hochbaum, D.S. (ed.): Approximation algorithms for NP-hard problems. PWS Publishing Co., Boston (1997)MATHGoogle Scholar
  9. 9.
    Hochbaum, D.S., Maass, W.: Approximation schemes for covering and packing problems in image processing and vlsi. J. ACM 32(1), 130–136 (1985)MathSciNetCrossRefMATHGoogle Scholar
  10. 10.
    Hristidis, V., Gravano, L., Papakonstantinou, Y.: Efficient ir-style keyword search over relational databases. In: VLDB, pp. 850–861 (2003)Google Scholar
  11. 11.
    Li, C., Ooi, B.C., Tung, A.K.H., Wang, S.: Dada: a data cube for dominant relationship analysis. In: SIGMOD, pp. 659–670 (2006)Google Scholar
  12. 12.
    Marian, A., Bruno, N., Gravano, L.: Evaluating top- queries over web-accessible databases. ACM Trans. Database Syst. 29(2), 319–362 (2004)CrossRefGoogle Scholar
  13. 13.
    Sun, Y., Han, J., Zhao, P., Yin, Z., Cheng, H., Wu, T.: Rankclus: integrating clustering with ranking for heterogeneous information network analysis. In: EDBT, pp. 565–576 (2009)Google Scholar
  14. 14.
    Wu, T., Li, X., Xin, D., Han, J., Lee, J., Redder, R.: Datascope: Viewing database contents in google maps’ way. In: VLDB, pp. 1314–1317 (2007)Google Scholar
  15. 15.
    Wu, T., Xin, D., Han, J.: Arcube: supporting ranking aggregate queries in partially materialized data cubes. In: SIGMOD Conference, pp. 79–92 (2008)Google Scholar
  16. 16.
    Wu, T., Xin, D., Mei, Q., Han, J.: Promotion analysis in multi-dimensional space. In: PVLDB (2009)Google Scholar
  17. 17.
    Xin, D., Han, J., Cheng, H., Li, X.: Answering top-k queries with multi-dimensional selections: The ranking cube approach. In: VLDB, pp. 463–475 (2006)Google Scholar
  18. 18.
    Zhang, T., Ramakrishnan, R., Livny, M.: Birch: A new data clustering algorithm and its applications. Data Min. Knowl. Discov. 1(2), 141–182 (1997)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Tianyi Wu
    • 1
  • Jiawei Han
    • 1
  1. 1.University of Illinois at Urbana-ChampaignUSA

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