Efficient evaluation of all-nearest-neighbor queries

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2007, Pages 1056-1065

  Yun, Chen ^a   Patel, Jignesh M ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA REDUCTION; DATA STRUCTURES; TREES (MATHEMATICS);

ALL NEAREST NEIGHBOUR (ANN) OPERATIONS; BUCKET QUADTREE INDEX STRUCTURES; MBA ALGORITHMS; PRUNING METRICES;

QUERY PROCESSING;

EID: 34548749756     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2007.368964     Document Type: Conference Paper

References (32)

1. The UCI Knowledge Discovery in Databases Archive. Downloadable from http://kdd.ics.uci.edu/.
2. Twin Astrographic Catalog Version 2 (TAC 2.0), 1999. Downloadable from http://ad.usno.navy.mil/tac/.
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, pages 322-331, 1990.
4. C. Böhm and F. Krebs. Supporting KDD Applications by the k-Nearest Neighbor Join. In DEXA, 2003.
5. C. Böhm and F. Krebs. The k-Nearest Neighbor Join: Turbo Charging the KDD Process. KAIS, 6(6), 2004.
6. B. Braunmüller, M. Ester, H.-P. Kriegel, and J. Sander. Efficiently Supporting Multiple Similarity Queries for Mining in Metric Databases. In ICDE, 2000.
7. M. Carey and et al. Shoring Up Persistent Applications. In SIGMOD, pages 383-394, 1994.
8. A. Corral, Y. Manolopoulos, Y Theodoridis, and M. Vassilakopoulos. Closest Pair Queries in Spatial Databases. In SIGMOD, pages 189-200, 2000.
9. A. Corral, Y. Manolopoulos, Y. Theodoridis, and M. Vassilakopoulos. Algorithms for Processing K-closest-pair queries in spatial databases. TKDE, 49(1):67-104, 2004.
10. D. J. Eisenstein and P. Hut. Hop: A new group-finding algorithm for n-body simulations. The Astrophysical Journal, 498:137-142, 1998.
11. I. Gargantini. An Effective Way to Represent Quadtrees. Commun. ACM, 25(12):905-910, 1982.
12. M. T. Goodrich, J.-J. Tsay, D. E. Vengroff, and J. S. Vitter. External-Memory Computational Geometry. In Proceedings of the 34th Annual Symposium on Foundations of Computer Science, pages 714-723, 1993.
13. G. R. Hjaltason and H. Samet. Incremental Distance Join Algorithms for Spatial Databases. In SIGMOD, 1998.
14. G. R. Hjaltason and H. Samet. Speeding up Construction of PMR Quadtree-based Spatial Indexes. VLDB Journal, 11(2): 109-137, 2002.
15. A. K. Jain, M. N. Murty, and P. J. Flynn. Data clustering: A review. ACM Computing Surveys, 31(3):264-323, 1999.
16. R. Jarvis and E. Patrick. Clustering using a similarity measure based on shared near neighbors. 22:1025-1034, 1973.
17. S. C. Johnson. Hierarchical clustering schemes. Psychometrika, 2:241-254, 1967.
18. S. Koenig and Y. Smirnov. Graph learning with a nearest neighbor approach. In Proceedings of the Conference on Computational Learning Theory, pages 19-28, 1996.
19. R. K. V. Kothuri, S. Ravada, and D. Abugov. Quadtree and R-tree Indexes in Oracle Spatial: A Comparison Using GIS Data. In SIGMOD, pages 546-557, 2002.
20. S. Leutenegger and M. Lopez. The Effect of Buffering on the Performance of R-trees. In IEEE TKDE, pages 33-44, 2000.
21. S. Šaltenis, C. Jensen, S. Leutenegger, and M. Lopez. Indexing the Positions of Continuously Moving Objects. In SIGMOD, pages 331-342, 2000.
22. R. Nock, M. Sebban, and D. Bernard. A simple locally adaptive nearest neighbor rule with application to pollution forecasting. Internal Journal of Pattern Recognition and Artificial Intelligence, 17(8): 1-14, 2003.
23. M. Pallavicini, C. Patrignani, M. Pontil, and A. Verri. The nearest-neighbor technique for particle identification. Nucl. Instr. and Meth., 405:133-138, 1998.
24. J. M. Patel and D. J. DeWitt. Partition Based Spatial-merge Join. In SIGMOD, pages 259-270, 1996.
25. H. Samet. The Quadtree and Related Hierarchical Data Structures. ACM Computing Surveys, 16(2): 187-260, 1984.
26. H. Shin, B. Moon, and S. Lee. Adaptive Multi-Stage Distance Join Processing. In SIGMOD, pages 343-354, 2000.
27. Y. Tao, D. Papadias, and J. Sun. The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries. In VLDB, pages 790-801, 2003.
28. Y. Theodoridis, J. R. O. Silva, and M. A. Nascimento. On the Generation of Spatiotemporal Datasets. Lecture Notes in Computer Science, 1651:147-164, 1999.
29. C. Xia, H. Lu, B. C. Ooi, and J. Hu. GORDER: An Efficient Method for KNN Join Processing. In VLDB, pages 756-767, 2004.
30. T. Xia, D. Zhang, E. Kanoulas, and Y. Du. On computing top-t most influential spatial sites. In VLDB, pages 946-957, 2005.
31. J. S. Yoo, S. Shekhar, and M. Celik. A join-less approach for co-location pattern mining: A summary of results. In IEEE International Conference on Data Mining(ICDM), 2005.
32. J. Zhang, N. Mamoulis, D. Papadias, and Y. Tao. All-Nearest-Neighbors Queries in Spatial Databases. In SSDBM, 2004.