On the least cost for proximity searching in metric spaces

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4007 LNCS, Issue , 2006, Pages 279-290

  Figueroa, Karina ^a,b   Chávez, Edgar ^a   Navarro, Gonzalo ^b   Paredes, Rodrigo ^b  

^a UNIVERSIDAD MICHOACANA DE SAN NICOLÁS DE HIDALGO   (Mexico)

^b UNIVERSITY OF CHILE   (Chile)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; COSTS; DATABASE SYSTEMS; PROBABILISTIC LOGICS; QUERY LANGUAGES;

DATABASE ELEMENTS; METRIC SPACES; PROBABILISTIC VERSION;

SEARCH ENGINES;

EID: 33746059374     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11764298_26     Document Type: Conference Paper

References (19)

1. S. Arya, D. Mount, N. Netanyahu, R. Silverman, and A. Wu. An optimal algorithm for approximate nearest neighbor searching in fixed dimension. In Proc. 5th ACM-SIAM Symposium on Discrete Algorithms (SODA '94), pages 573-583, 1994.
2. R. Baeza-Yates and B. Ribeiro. Modern Information Retrieval. Addison-Wesley, 1999.
3. C. Böhm, S. Berchtold, and D. A. Keim. Searching in high-dimensional spaces-index structures for improving the performance of multimedia databases. ACM Computing Surveys, 33(3):322-373, 2001.
4. B. Bustos and G. Navarro. Probabilistic proximity search algorithms based on compact partitions. Journal of Discrete Algorithms (JDA), 2(1):115-134, 2003.
5. E. Chávez, K. Figueroa, and G. Navarro. Proximity searching in high dimensional spaces with a proximity preserving order. In MICAI 2005: Advances in Artificial Intelligence, volume 3789 of LNCS, pages 405-414, 2005.
6. E. Chávez and G. Navarro. Probabilistic proximity search: Fighting the curse of dimensionality in metric spaces. Information Processing Letters, 85(1):39-46, 2003.
7. E. Chávez, G. Navarro, R. Baeza-Yates, and J. Marroquín. Proximity searching in metric spaces. ACM Computing Surveys, 33(3):273-321, 2001.
8. P. Ciaccia and M. Patella. Searching in metric spaces with user-defined and approximate distances. ACM Trans. on Database Systems, 27(4):398-437, 2002.
9. K. Clarkson. Nearest neighbor queries in metric spaces. Discrete Computational Geometry, 22(1):63-93, 1999.
10. R. Fagin, R. Kumar, and D. Sivakumar. Comparing top k lists. SIAM J. Discrete Math, 17(1):134-160, 2003.
11. K. Fredriksson. Parallel and memory adaptive metric indexes. Pattern Recognition Letters, to appear.
12. L. Micó, J. Oncina, and R. Carrasco. A fast branch and bound nearest neighbour classifier in metric spaces. Pattern Recognition Letters, 17:731-739, 1996.
13. L. Micó, J. Oncina, and E. Vidal. A new version of the nearest-neighbor approximating and eliminating search (AESA) with linear preprocessing-time and memory requirements. Pattern Recognition Letters, 15:9-17, 1994.
14. P. Navarrete and J. Ruiz-Del-Solar. Analysis and comparison of eigenspace-based face recognition approaches. Int. Journal of Pattern Recognition and Artificial Intelligence, 16(7):817-830, 2002.
15. G. Navarro, R. Paredes, and E. Chávez. t-spanners as a data structure for metric space searching. In SPIRE 2002: 9th International Symposium on String Processing and Information Retrieval, LNCS 2476, pages 298-309, 2002.
16. P. Phillips, H. Wechsler, J. Huang, and P. Rauss. The FERET database and evaluation procedure for face recognition algorithms. Image and Vision Computing Journal, 16(5):295-306, 1998.
17. E. Vidal. An algorithm for finding nearest neighbors in (approximately) constant average time. Pattern Recognition Letters, 4:145-157, 1986.
18. J. Vilar. Reducing the overhead of the AESA metric-space nearest neighbor searching algorithm. Information Processing Letters, 56:256-271, 1995.
19. D. White and R. Jain. Algorithms and strategies for similarity retrieval. Technical Report VCL-96-101, Visual Computing Laboratory, U. of California, 1996.