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Toward efficient multidimensional subspace skyline computation

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Abstract

Skyline queries have attracted considerable attention to assist multicriteria analysis of large-scale datasets. In this paper, we focus on multidimensional subspace skyline computation that has been actively studied for two approaches. First, to narrow down a full-space skyline, users may consider multiple subspace skylines reflecting their interest. For this purpose, we tackle the concept of a skycube, which consists of all possible non-empty subspace skylines in a given full space. Second, to understand diverse semantics of subspace skylines, we address skyline groups in which a skyline point (or a set of skyline points) is annotated with decisive subspaces. Our primary contributions are to identify common building blocks of the two approaches and to develop orthogonal optimization principles that benefit both approaches. Our experimental results show the efficiency of proposed algorithms by comparing them with state-of-the-art algorithms in both synthetic and real-life datasets.

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Notes

  1. http://orpailleur.loria.fr/index.php/Software.

  2. http://www.nba.com.

  3. http://www.ipums.org.

References

  1. Bartolini, I., Ciaccia, P., Patella, M.: Efficient sort-based skyline evaluation. ACM Trans. Database Syst. 33(4), 31–79 (2008)

    Article  Google Scholar 

  2. Bentley, J.L., Clarkson, K.L., Levine, D.B.: Fast linear expected-time algorithms for computing maxima and convex hulls. In: SODA, pp. 179–187 (1990)

  3. 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  MATH  MathSciNet  Google Scholar 

  4. Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: ICDE, pp. 421–430 (2001)

  5. Chomicki, J., Godfery, P., Gryz, J., Liang, D.: Skyline with presorting. In: ICDE, pp. 717–719 (2003)

  6. Godfrey, P., Shipley, R., Gryz, J.: Maximal vector computation in large data sets. In: VLDB, pp. 229–240 (2005)

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

    Article  Google Scholar 

  8. Kailasam, G.T., Lee, J., Rhee, J.-W., Kang, J.: Efficient skycube computation using point and domain-based filtering. Inf. Sci. 180(7), 1090–1103 (2010)

    Article  Google Scholar 

  9. Kossmann, D., Ramsak, F., Rost, S.: Shooting stars in the sky: an online algorithm for skyline queries. In: VLDB, pp. 275–286 (2002)

  10. Kung, H.T., Luccio, F., Preparata, F.P.: On finding the maxima of a set of vectors. J. ACM 22(4), 469–476 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  11. Lee, J., Hwang, S.: BSkyTree: Scalable skyline computation using a balanced pivot selection. In: EDBT, pp. 195–206 (2010)

  12. Lee, J., Hwang, S.: QSkycube: efficient skycube computation using point-based space partitioning. Proc. VLDB Endow. 4(3), 185–196 (2010)

    Google Scholar 

  13. Lee, K.C., Zheng, B., Li, H., Lee, W.-C.: Approaching the skyline in Z order. In: VLDB, pp. 279–290 (2007)

  14. Lee, K.C.K., Lee, W.-C., Zheng, B., Li, H., Tian, Y.: Z-SKY: an efficient skyline query processing framework based on Z-order. VLDB J. 19(3), 333–362 (2010)

    Article  Google Scholar 

  15. Papadias, D., Tao, Y., Fu, G., Seeger, B.: An optimal and progressive algorithm for skyline queries. In: SIGMOD, pp. 467–478 (2003)

  16. Pei, J., Fu, A.W., Lin, X., Wang. H.: Computing compressed multidimensional skyline cubes efficiently. In: ICDE, pp. 96–105 (2007)

  17. Pei, J., Jin, W., Ester, M., Tao, Y.: Catching the best views of skyline: a semantic approach based on decisive subspaces. In: VLDB, pp. 253–264 (2005)

  18. Pei, J., Yuan, Y., Lin, X., Jin, W., Ester, M., Liu, Q., Wang, W., Tao, Y., Yu, J.X., Zhang, Q.: Towards multidimensional subspace skyline analysis. ACM Trans. Database Syst. 31(4), 1335–1381 (2006)

    Article  Google Scholar 

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

    Google Scholar 

  20. Tan K., Eng P., Ooi, B.C.: Efficient progressive skyline computation. In: VLDB, pp. 301–310 (2001)

  21. Tao, Y., Xiao, X., Pei, J.: SUBSKY: efficient computation of skylines in subspaces. In: ICDE, pp. 65–74 (2006)

  22. Tao, Y., Xiao, X., Pei, J.: Efficient skyline and top-k retrieval in subspaces. IEEE Trans. Knowl. Data Eng. 19(8), 1072–1088 (2007)

    Article  Google Scholar 

  23. Vlachou, A., Doulkeridis, C., Kotidis, Y., Vazirgiannis, M.: SKYPEER: efficient subspace skyline computation over distributed data. In: ICDE, pp. 416–425 (2007)

  24. Xia, T., Zhang, D.: Refreshing the sky: the compressing skycube with efficient support for frequent updates. In: SIGMOD, pp. 491–502 (2006)

  25. Yiu, M.L., Lo, E., Yung, D.: Measuring the sky: on computing data cubes via skylining the measures. IEEE Trans. Knowl. Data Eng. 24(3), 492–505 (2012)

    Article  Google Scholar 

  26. Yuan, Y., Lin, X., Liu, Q., Wang, W., Yu, J.X., Zhang, Q.: Efficient computation of the skyline cube. In: VLDB, pp. 241–252 (2005)

  27. Zhang, S., Mamoulis, N., Cheung, D.W.: Scalable skyline computation using object-based space partitioning. In: SIGMOD, pp. 483–494 (2009)

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Acknowledgments

This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, and Microsoft Research, under IT/SW Creative research program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2012-H0503- 12-1036).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea

    Jongwuk Lee & Seung-won Hwang

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  1. Jongwuk Lee
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  2. Seung-won Hwang
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Correspondence to Seung-won Hwang.

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Lee, J., Hwang, Sw. Toward efficient multidimensional subspace skyline computation. The VLDB Journal 23, 129–145 (2014). https://doi.org/10.1007/s00778-013-0317-y

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