Where are you heading, metric access methods? A provocative survey

Proceedings - 3rd International Conference on SImilarity Search and APplications, SISAP 2010

Volumn , Issue , 2010, Pages 13-21

  Skopal, Tomáš ^a  

^a CHARLES UNIVERSITY   (Czech Republic)

Author keywords

Content based search; MAM; Metric access methods; Similarity

Indexed keywords

CONTENT-BASED; CONTENT-BASED SEARCH; KEYWORD SEARCH; MAM; METRIC ACCESS METHODS; METRIC DISTANCES; METRIC MODEL; METRIC SPACE MODEL; REAL-WORLD; REAL-WORLD APPLICATION; SIMILARITY; SIMILARITY QUERY; SIMILARITY SEARCH;

INDEXING (OF INFORMATION); INFORMATION RETRIEVAL; TOPOLOGY;

SEARCH ENGINES;

EID: 78649869041     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1862344.1862347     Document Type: Conference Paper

References (26)

1. S. F. Altschul, T. L. Madden, A. A. Schaffer, J. Zhang, Z. Zhang, W. Miller, and D. J. Lipman. Gapped blast and psi-blast: a new generation of protein database search programs. Nucleic Acids Res., 25:3389-3402, 1997.
2. R. A. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley Longman Publishing, 1999.
3. S. Berretti, A. D. Bimbo, and P. Pala. Retrieval by shape similarity with perceptual distance and effective indexing. IEEE Transactions on Multimedia, 2(4):225-239, 2000.
4. C. Böhm, S. Berchtold, and D. Keim. Searching in High-Dimensional Spaces - Index Structures for Improving the Performance of Multimedia Databases. ACM Computing Surveys, 33(3):322-373, 2001.
5. E. Chávez and G. Navarro. A Probabilistic Spell for the Curse of Dimensionality. In ALENEX'01, LNCS 2153, pages 147-160. Springer, 2001.
6. E. Chávez, G. Navarro, R. Baeza-Yates, and J. L. Marroquín. Searching in metric spaces. ACM Computing Surveys, 33(3):273-321, 2001.
7. L. Chen and X. Lian. Efficient processing of metric skyline queries. IEEE Trans. on Knowl. and Data Eng., 21(3):351-365, 2009.
8. P. Ciaccia, M. Patella, and P. Zezula. M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In VLDB'97, pages 426-435, 1997.
9. P. Ciaccia, M. Patella, and P. Zezula. Processing complex similarity queries with distance-based access methods. In H.-J. Schek, F. Saltor, I. Ramos, and G. Alonso, editors, Advances in Database Technology - EDBT'98, 6th International Conference on Extending Database Technology, Valencia, Spain, March 23-27, 1998, Proceedings, volume 1377 of Lecture Notes in Computer Science, pages 9-23. Springer, 1998.
10. R. Datta, D. Joshi, J. Li, and J. Z. Wang. Image retrieval: Ideas, inuences, and trends of the new age. ACM Computing Surveys, 40(2):1-60, 2008.
11. A. Eckhardt, T. Skopal, and P. Vojtáš. On fuzzy vs. metric similarity search in complex databases. In Proc. 8th Conference on Flexible Query Answering Systems (FQAS'09), volume 5822 of LNAI, pages 64-75. Springer, 2009.
12. R. Fagin. Combining fuzzy information from multiple systems. J. Comput. Syst. Sci., 58(1):83-99, 1999.
13. M. L. Hetland. The basic principles of metric indexing. In Swarm Intelligence for Multi-objective Problems in Data Mining. Springer, 2009.
14. M. L. Hetland. Ptolemaic indexing. CoRR, abs/0911.4384, 2009.
15. G. Hjaltason and H. Samet. Incremental similarity search in multimedia databases, Comp. Science Dept. TR-4199, Univ. of Maryland, College Park, 2000.
16. W. H. Hsu, L. S. Kennedy, and S.-F. Chang. Reranking methods for visual search. IEEE Multimedia, 14:14-22, 2007.
17. E. Keogh, L. Wei, X. Xi, S.-H. Lee, and M. Vlachos. LB-Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures. In VLDB '06: Proceedings of the 32nd international conference on Very large data bases, pages 882-893. VLDB Endowment, 2006.
18. M. L. Mico, J. Oncina, and E. Vidal. A new version of the nearest-neighbour approximating and eliminating search algorithm (AESA) with linear preprocessing time and memory requirements. Pattern Recogn. Lett., 15(1):9-17, 1994.
19. J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. In IEEE Conference on Computer Vision and Pattern Recognition. CVPR '07, pages 1-8, 2007.
20. H. Samet. Foundations of Multidimensional and Metric Data Structures. Morgan Kaufmann, 2006.
21. T. Skopal. Unified framework for fast exact and approximate search in dissimilarity spaces. ACM Transactions on Database Systems, 32(4):1-46, 2007.
22. T. Skopal and B. Bustos. On Nonmetric Similarity Search Problems in Complex Domains. ACM Computing Surveys 44(3), 2012, issue tentative, available at http://siret.ms.mff.cuni.cz/skopal/pub/nmsurvey.pdf.
23. T. Smith and M. Waterman. Identification of common molecular subsequences. Journal of Molecular Biology, 147(1):195-197, 1981.
24. Wikipedia. List of content-based image retrieval engines http://en.wikipedia.org/wiki/List-of-CBIR-engines, June 16, 2010.
25. L. Ye and E. Keogh. Time series shapelets: a new primitive for data mining. In KDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 947-956, New York, NY, USA, 2009. ACM.
26. P. Zezula, G. Amato, V. Dohnal, and M. Batko. Similarity Search: The Metric Space Approach (Advances in Database Systems). Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2005.