Approximate voronoi cell computation on spatial data streams

VLDB Journal

Volumn 18, Issue 1, 2009, Pages 57-75

  Sharifzadeh, Mehdi ^a   Shahabi, Cyrus ^a  

^a University of Southern California   (United States)

Author keywords

Approximation; Sliding window; Spatial data stream; Voronoi cell

Indexed keywords

APPROXIMATION; BASIC BUILDING BLOCKS; CLASSIC ALGORITHMS; D SPACES; DATA SETS; DATA STREAMS; MEMORY REQUIREMENTS; NEAREST NEIGHBOR SEARCHES; REALISTIC SCENARIOS; SAMPLE SIZES; SLIDING WINDOW; SPATIAL DATA STREAM; STREAMING ALGORITHMS; VARIATIONS OF; VORONOI CELL; VORONOI DIAGRAMS; WINDOW SIZES;

APPROXIMATION ALGORITHMS; DECODING; POLYNOMIAL APPROXIMATION; WINDOWS;

DATA MINING;

EID: 58149472578     PISSN: 10668888     EISSN: 0949877X     Source Type: Journal    
DOI: 10.1007/s00778-007-0081-y     Document Type: Article

References (25)

1. Arya, S., Malamatos, T., Mount, D.M.: Space-efficient approximate voronoi diagrams. In: Proceedings of the 34th ACM Symp. on Theory of Computing (STOC), pp. 721-730 (2002)
2. Arya, S., Vigneron, A.: Approximating a voronoi cell. Tech. rep. (2003). HKUST-TCSC-2003-10
3. Banaei-Kashani, F., Shahabi, C.: SWAM: A family of access methods for similarity-search in peer-to-peer data networks. In: Proceedings of the Thirteenth Conference on Information and Knowledge Management (CIKM'04), pp. 304-313 (2004)
4. de Berg, M., van Kreveld, M., Overmars, M., Schwarzkopf, O.: Computational Geometry: Algorithms and Applications, 2nd edn. Springer, Heidelberg (2000)
5. Cormode, G., Muthukrishnan, S.: Radial histograms for spatial streams. DIMACS TR 2003-11 (2003) (in press)
6. Feigenbaum, J., Kannan, S., Zhang, J.: Computing diameter in the streaming and sliding-window models. Algorithmica (2004) (in press)
7. Gardner, M.: The Sixth Book of Mathematical Games from Scientific American. University of Chicago Press (1984)
8. Hagedoorn, M.: Nearest neighbors can be found efficiently if the dimension is small relative to the input size. In: Proceedings of the 9th International Conference on Database Theory - ICDT 2003, Lecture Notes in Computer Science, vol. 2572, pp. 440-454. Springer, Heidelberg (2003)
9. Har-Peled, S.: A replacement for voronoi diagrams of near linear size. In: Proc. 42nd Annu. IEEE Sympos. Found. Comput. Sci., pp. 94-103 (2001)
10. Hershberger, J., Shrivastava, N., Suri, S.: Cluster hull: A technique for summarizing spatial data streams. In: Proceedings of 22nd IEEE Conf. Data Engineering, ICDE'06. IEEE Computer Society (2006)
11. Hershberger, J., Suri, S.: Adaptive sampling for geometric problems over data streams. In: Proceedings of the Twenty-third ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems. ACM (2004)
12. Indyk, P.: Algorithms for dynamic geometric problems over data streams. In: Proceedings of the Thirty-Sixth annual ACM Symposium on Theory of Computing, pp. 373-380. ACM Press (2004). doi:10.1145/1007352.1007413
13. Indyk, P.: Streaming algorithms for geometric problems. In: Proceedings of the 16th Canadian Conference on Computational Geometry (CCCG'04) (2004). Invited Talk
14. Kolahdouzan, M.R., Shahabi, C.: Voronoi-based k nearest neighbor search for spatial network databases. In: Proceedings of the 30th International Conference on Very Large Data Bases (VLDB'04) (2004)
15. Korn, F., Muthukrishnan, S.: Influence sets based on reverse nearest neighbor queries. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of data, pp. 201-212. ACM Press (2000). doi:10.1145/342009.335415
16. Lin, X., Yuan, Y., Wang, W., Lu, H.: Stabbing the sky: efficient skyline computation over sliding windows. In: Proceedings of the 21st International Conference on Data Engineering (ICDE'05), pp. 502-513. IEEE Computer Society (2005)
17. Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge University Press (1995)
18. Muthukrishnan, S.: Data streams: algorithms and applications. Tech. rep., Computer Science Department, Rutgers University (2003)
19. Okabe, A., Boots, B., Sugihara, K., Chiu, S.N.: Spatial Tessellations, Concepts and Applications of Voronoi Diagrams, 2nd edn. Wiley, New York (2000)
20. Seidel, R., Aragon, C.R.: Randomized search trees. Algorithmica 16(4/5), 464-497 (1996)
21. Sharifzadeh, M., Shahabi, C.: Supporting spatial aggregation in sensor network databases. In: Proceedings of the 12th ACM International Symposium on Advances in Geographic Information Systems, pp. 166-175 (2004)
22. Sharifzadeh, M., Shahabi, C.: Utilizing Voronoi cells of location data streams for accurate computation of aggregate functions in sensor networks. GeoInformatica 10(1), 9-36 (2005)
23. Stanoi, I., Agrawal, D., Abbadi, A.E.: Reverse nearest neighbor queries for dynamic databases. In: ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp. 44-53 (2000)
24. Stanoi, I., Riedewald, M., Agrawal, D., Abbadi, A.E.: Discovery of influence sets in frequently updated databases. In: Proceedings of the 27th International Conference on Very Large Data Bases (VLDB'01), pp. 99-108. Morgan Kaufmann Publishers Inc. (2001)
25. Zhang, J., Zhu, M., Papadias, D., Tao, Y., Lee, D.L.: Location-based spatial queries. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 443-454. ACM Press (2003). doi: 10.1145/872757. 872812