Similarity search on bregman divergence: Towards non-metric indexing

Proceedings of the VLDB Endowment

Volumn 2, Issue 1, 2009, Pages 13-24

  Zhang, Zhenjie ^a   Ooi, Beng Chin ^a   Parthasarathy, Srinivasan ^b   Tung, Anthony K H ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b OHIO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; INDEXING (OF INFORMATION); NEAREST NEIGHBOR SEARCH; SET THEORY; SPEECH RECOGNITION; TIME SERIES; TIME SERIES ANALYSIS; TOPOLOGY; TREES (MATHEMATICS); VECTOR SPACES;

BREGMAN DIVERGENCES; DISTANCE FUNCTIONS; HIGH DIMENSIONAL DATASETS; IMPROVED DISTANCE; INDEX CONSTRUCTION; ITAKURA-SAITO DISTANCES; TRIANGLE INEQUALITY; VECTOR APPROXIMATION FILES;

QUERY PROCESSING;

EID: 77956960464     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/1687627.1687630     Document Type: Article

References (26)

1. S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu. An optimal algorithm for approximate nearest neighbor searching fixed dimensions. J. ACM, 45(6):891-923, 1998.
2. A. Banerjee, S. Merugu, I. S. Dhillon, and J. Ghosh. Clustering with bregman divergences. Journal of Machine Learning Research, 6:1705-1749, 2005.
3. N. Beckmann, H.-P. Kriegel, R. Schneider, and B. Seeger. The r*-tree: An efficient and robust access method for points and rectangles. In SIGMOD Conference, pages 322-331, 1990.
4. A. Beygelzimer, S. Kakade, and J. Langford. Cover trees for nearest neighbor. In ICML, pages 97-104, 2006.
5. S. Boltz, E. Debreuve, and M. Barlaud. High dimensional statistical distance for region-of-interest tracking: Application to combining a soft geometric constraint with radiometry. In CVPR, 2007.
6. L. Bregman. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming. USSR Computational Mathematics and Mathematical Physics, 7(3):200-217, 1967.
7. L. Cayton. Fast nearest neighbor retrieval for bregman divergences. In ICML, pages 112-119, 2008.
8. L. Chen and X. Lian. Efficient similarity search in nonmetric spaces with local constant embedding. IEEE Trans. Knowl. Data Eng., 20(3):321-336, 2008.
9. H. Ferhatosmanoglu, E. Tuncel, D. Agrawal, and A. E. Abbadi. Vector approximation based indexing for non-uniform high dimensional data sets. In CIKM, pages 202-209, 2000.
10. J. H. Friedman, J. L. Bentley, and R. A. Finkel. An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Softw., 3(3):209-226, 1977.
11. J. Goldberger, S. Gordon, and H. Greenspan. An efficient image similarity measure based on approximations of kl-divergence between two gaussian mixtures. In ICCV, pages 487-493, 2003.
12. R. M. Gray, A. Buzo, A. H. Gray, and Y. Matsuyama. Disotrotion measures for speech processing. IEEE Transaction on Acoustics, Speech, and Signal Processing, 28(4).
13. A. Guttman. R-trees: A dynamic index structure for spatial searching. In SIGMOD Conference, pages 47-57, 1984.
14. F. Itakura and S. Saito. A statistical method for estimation of speech spectral density and formant frequencies. Electronics and Communications in Japan, 53:36-43, 1970.
15. H. V. Jagadish, B. C. Ooi, K.-L. Tan, C. Yu, and R. Zhang. idistance: An adaptive b+-tree based indexing method for nearest neighbor search. ACM Trans. Database Syst., 30(2):364-397, 2005.
16. B. Kulis, M. Sustik, and I. Dhillon. Learning low-rank kernel matrices. In ICML, pages 505-512, 2006.
17. B. Long, Z. M. Zhang, and P. S. Yu. Graph partitioning based on link distributions. In AAAI, pages 578-583, 2007.
18. G. McLachlan and D. Peel. Finite Mixture Models. Wiley-Interscience, 2000.
19. F. Nielsen and R. Nock. On approximating the smallest enclosing bregman balls. In Symposium on Computational Geometry, pages 485-486, 2006.
20. F. C. N. Pereira, N. Tishby, and L. Lee. Distributional clustering of english words. In ACL, pages 183-190, 1993.
21. J. Puzicha, Y. Rubner, C. Tomasi, and J. M. Buhmann. Empirical evaluation of dissimilarity measures for color and texture. In ICCV, pages 1165-1172, 1999.
22. N. Rasiwasia, P. Moreno, and N. Vasconcelos. Bridging the gap: Query by semantic example. IEEE Transaction on Multimedia, 9(5).
23. D. Suciu and N. N. Dalvi. Foundations of probabilistic answers to queries. In SIGMOD Conference, 2005.
24. J. Tang, X.-S. Hua, G.-J. Qi, Y. Song, and X. Wu. Video annotation based on kernel linear neighborhood propagation. IEEE Transaction on Multimedia, 4(10):620-628, 2008.
25. A. K. H. Tung, R. Zhang, N. Koudas, and B. C. Ooi. Similarity search: A matching based approach. In VLDB, pages 631-642, 2006.
26. R. Weber, H.-J. Schek, and S. Blott. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In VLDB, pages 194-205, 1998.