Efficient skyline retrieval with arbitrary similarity measures

Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09

Volumn , Issue , 2009, Pages 1052-1063

  Deepak, P ^a   Deshpande, Prasad M ^a   Majumdar, Debapriyo ^a   Krishnapuram, Raghu ^a  

^a IBM RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CANDIDATE SETS; DATA DISTRIBUTION; DISK ACCESS COST; LOWER BOUNDS; METRIC SPACES; NON-METRIC SPACES; ON-LINE ALGORITHMS; ORDERS OF MAGNITUDE; PRIOR KNOWLEDGE; RESPONSE TIME; SIMILARITY MEASURE; SKYLINE QUERY; STATE-OF-THE-ART ALGORITHMS; TREE-BASED ALGORITHMS;

ALGORITHMS; COMPUTATIONAL EFFICIENCY; CONTROL THEORY; DATABASE SYSTEMS; INDEXING (OF INFORMATION); MIDDLEWARE; TOPOLOGY;

SET THEORY;

EID: 70349127599     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1516360.1516480     Document Type: Conference Paper

References (21)

1. How fast is your disk? http://www.linuxinsight.com/how-fast-is-your- disk.html, January 2007.
2. A. Asuncion and D. Newman. UCI machine learning repository, 2007.
3. W.-T. Balke, U. Güntzer, and J. X. Zheng. Efficient distributed skylining for web information systems. In EDBT, pages 256-273, 2004.
4. H. Bast, D. Majumdar, R. Schenkel, M. Theobald, and G. Weikum. Io-top-k: Index-access optimized top-k query processing. In VLDB. ACM, 2006.
5. J. L. Bentley. Multidimensional binary search trees used for associative searching. Commun. ACM, 18(9):509-517, 1975.
6. S. Börzsönyi, D. Kossmann, and K. Stocker. The skyline operator. In ICDE, 2001.
7. J. Chomicki, P. Godfrey, J. Gryz, and D. Liang. Skyline with presorting. In ICDE, 2003.
8. W. Chung, Gray and Horst. Windows 2000 disk io performance. Microsoft Research TR, June 2000.
9. K. Deng, X. Zhou, and H. T. Shen. Multi-source skyline query processing in road networks. In ICDE, 2007.
10. P. Deshpande, Deepak, and K. Kummamuru. Efficient online top-k retrieval with arbitrary similarity measures. In EDBT, 2008.
11. R. Fagin, A. Lotem, and M. Naor. Optimal aggregation algorithms for middleware. In PODS. ACM, 2001.
12. R. Fagin, A. Lotem, and M. Naor. Optimal aggregation algorithms for middleware. J. Comput. Syst. Sci., 66(4):614-656, 2003.
13. P. Godfrey, R. Shipley, and J. Gryz. Maximal vector computation in large data sets. In VLDB, 2005.
14. K. Goh, B. Li, and E. Chang. Dyndex: A dynamic and nonmetric space indexer. In ACM Intl. Conference on Multimedia, 2002.
15. D. Kossmann, F. Ramsak, and S. Rost. Shooting stars in the sky: An online algorithm for skyline queries. In VLDB, pages 275-286. Morgan Kaufmann, 2002.
16. D. Papadias, Y. Tao, G. Fu, and B. Seeger. An optimal and progressive algorithm for skyline queries. In SIGMOD Conference, 2003.
17. D. Papadias, Y. Tao, G. Fu, and B. Seeger. Progressive skyline computation in database systems. ACM Trans. Database Syst., 30(l):41-82, 2005.
18. K.-L. Tan, P.-K. Eng, and B. C. Ooi. Efficient progressive skyline computation. In VLDB, pages 301-310. Morgan Kaufmann, 2001.
19. Y. Tao, X. Xiao, and J. Pei. Subsky: Efficient computation of skylines in subspaces. In ICDE, page 65. IEEE Computer Society, 2006.
20. S. Wang, B. C. Ooi, A. K. H. Tung, and L. Xu. Efficient skyline query processing on peer-to-peer networks. In ICDE, pages 1126-1135, 2007.
21. P. Zesula, G. Amato, V. Dohnal, and M. Batko. Similarity Search - The Metric Space Approach. Springer, 2005.