Query-sensitive embeddings

Proceedings of the ACM SIGMOD International Conference on Management of Data

Volumn , Issue , 2005, Pages 706-717

  Athitsos, Vassilis ^a   Hadjieleftheriou, Marios ^a   Kollios, George ^a   Sclaroff, Stan ^a  

^a BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTATION THEORY; CONFORMAL MAPPING; DATABASE SYSTEMS; INFORMATION RETRIEVAL; QUERY LANGUAGES; TIME SERIES ANALYSIS;

NEAREST NEIGHBOR RETRIEVAL; QUERY-SENSITIVE EMBEDDINGS; TIME-SERIES DATABASES; VECTOR SPACES;

EMBEDDED SYSTEMS;

EID: 29844444238     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1066157.1066238     Document Type: Conference Paper

References (40)

1. C. C. Aggarwal. Re-designing distance functions and distance-based applications for high dimensional data. SIGMOD Record, 30(1):13-18, 2001.
2. V. Athitsos, J. Alon, S. Sclaroff, and G. Kollios. BoostMap: A method for efficient approximate similarity rankings. In CVPR, 2004.
3. H. Barrow, J. Tenenbaum, R. Belles, and H. Wolf, Parametric correspondence and chamfer matching: Two new techniques for image matching. In IJCAI, pages 659-663, 1977.
4. S. Belongie, J. Malik, and J. Puzicha. Matching shapes. In ICCV, volume 1, pages 454-461, 2001.
5. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. PAMI, 24(4):509-522, 2002.
6. 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.
7. J. Bourgain, On Lipschitz embeddings of finite metric spaces in Hilbert space. Israel Journal of Mathematics, 52:46-52, 1985.
8. T. Bozkaya and Z. Özsoyoglu. Indexing large metric spaces for similarity search queries. ACM Trans. Database Syst., 24(3):361-404, 1999.
9. K. Chakrabarti and S. Mehrotra. Local dimensionality reduction: A new approach to indexing high dimensional spaces. In VLDB, pages 89-100, 2000.
10. C. Domeniconi, J. Peng, and D. Gunopulos, Locally adaptive metric nearest-neighbor classification. PAMI, 24(9):1281-1285, 2002.
11. Ö. Egecioglu and H. Ferhatosmanoglu. Dimensionality reduction and similarity distance computation by inner product approximations. In International Conference on Information and Knowledge Management, pages 219-226, 2000.
12. C. Faloutsos and K. Lin. FastMap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets. In ACM SIGMOD, pages 163-174, 1995.
13. A. Gionis, P. Indyk, and R. Motwani. Similarity search in high dimensions via. hashing. In VLDB, pages 518-529, 1999.
14. T. Hastie and R. Tibshirani. Discriminant adaptive nearest-neighbor classification. PAMI, 18(6):607-616, 1996.
15. G. Hjaltason and H. Samet. Properties of embedding methods for similarity searching in metric spaces. PAMI, 25(5):530-549, 2003.
16. G. Hristescu and M. Farach-Colton. Cluster-preserving embedding of proteins. Technical Report 99-50, CS Department, Rutgers University, 1999.
17. P. Indyk. High-dimensional Computational Geometry. PhD thesis, Stanford University, 2000.
18. C. T. Jr., A. Traina, B. Seeger, and C. Faloutsos. Slim-trees: High performance metric trees minimizing overlap between nodes. In 7th International Conference on Extending Database Technology (EDBT), pages 51-65, 2000.
19. K. V. R. Kanth, D. Agrawal, and A. Singh. Dimensionality reduction for similarity searching in dynamic databases. In ACM SIGMOD International Conference on Management of Data, pages 166-176, 1998.
20. E. Keogh. Exact indexing of dynamic time warping. In VLDB, pages 406-417, 2002.
21. N. Koudas, B. C. Ooi, H. T. Shen, and A. K. H. Tung. Ldc: Enabling search by partial distance in a hyper-dimensional space. In ICDE, pages 6-17, 2004.
22. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278-2324, 1998.
23. C. Li, E. Chang, H. Garcia-Molina, and G. Wiederhold, Clustering for approximate similarity search in high-dimensional spaces. IEEE TKDE, 14(4):792-808, 2002.
24. S. Roweis and L. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290:2323-2326, 2000.
25. S. C. Sahinalp, M. Tasan, J. Macker, and Z. M. Özsoyoglu. Distance based indexing for string proximity search. In ICDE, pages 125-136, 2003.
26. Y. Sakurai, M. Yoshikawa, S. Uemura, and H. Kojima. The A-tree: An index structure for high-dimensional spaces using relative approximation. In VLDB, pages 516-526, 2000.
27. R. Schapire and Y. Singer. Improved boosting algorithms using confidence-rated predictions. Machine Learning, 37(3):297-336, 1999.
28. J. Tenenbaum, V. d. Silva, and J. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290:2319-2323, 2000.
29. K. Tieu and P. Viola. Boosting image retrieval. In CVPR, pages 228-235, 2000.
30. E. Tuncel, H. Ferhatosmanoglu, and K. Rose. Vq-index: An index structure for similarity searching in multimedia databases. In Proc. of ACM Multimedia, pages 543-552, 2002.
31. P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features. In CVPR, volume 1, pages 511-518, 2001.
32. M. Vlachos, M. Hadjieleftheriou, D. Gunopulos, and E. Keogh. Indexing multi-dimensional time-series with support for multiple distance measures. In Proc. of ACM SIGKDD, pages 216-225, 2003.
33. X. Wang, J. Wang, K. Lin, D. Shasha, B. Shapiro, and K. Zhang. An index structure for data mining and clustering. Knowledge and Information Systems, 2(2):161-184, 2000.
34. R. Weber and K. Bohm. Trading quality for time with nearest-neighbor search. In International Conference on Extending Database Technology: Advances in Database Technology, pages 21-35, 2000.
35. 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.
36. D. White and R. Jain. Similarity indexing: Algorithms and performance. In Storage and Retrieval for Image and Video Databases (SPIE), pages 62-73, 1996.
37. B.-K. Yi, H. V. Jagadish, and C. Faloutsos. Efficient retrieval of similar time sequences under time warping. In Proc. of ICDE, pages 201-208, 1998.
38. P. Yianilos. Data structures and algorithms for nearest neighbor search in general metric spaces. In ACM-SIAM Symposium on Discrete Algorithms, pages 311-321, 1993.
39. F. Young and R. Hamer. Multidimensional Scaling: History, Theory and Applications. Lawrence Erlbaum Associates, Hillsdale, New Jersey, 1987.
40. P. Zezula, P. Savino, G. Amato, and F. Rabitti. Approximate similarity retrieval with M-trees. The VLDB Journal, 4:275-293, 1998.