Efficient temporal counting with bounded error

VLDB Journal

Volumn 17, Issue 5, 2008, Pages 1271-1292

  Tao, Yufei ^a   Xiao, Xiaokui ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Aggregate search; Approximate query processing; Temporal database

Indexed keywords

EID: 46749123178     PISSN: 10668888     EISSN: 0949877X     Source Type: Journal    
DOI: 10.1007/s00778-007-0066-x     Document Type: Article

References (40)

1. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules, pp. 307-328 (1996)
2. Agrawal, R., Srikant, R.: Privacy-preserving data mining. In: SIGMOD, pp. 439-450 (2000)
3. Arasu, A., Manku, G.S.: Approximate counts and quantiles over sliding windows. In: PODS, pp. 286-296 (2004)
4. Arge L. and Vahrenhold J. (2004). I/O-efficient dynamic planar point location. Comput. Geom. 29(2): 147-162
5. Becker B., Gschwind S., Ohler T., Seeger B. and Widmayer P. (1996). An asymptotically optimal multiversion b-tree. VLDB J. 5(4): 264-275
6. Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: an efficient and robust access method for points and rectangles. In: SIGMOD, pp. 322-331 (1990)
7. Berg M., Kreveld M., Overmars M. and Schwarzkopf O. (2000). Comput. Geom. Algorithms and Appl. Springer, Heidelberg
8. Bohlen, M.H., Gamper, J., Jensen, C.S.: Multi-dimensional aggregation for temporal data. In: EDBT, pp. 257-275 (2006)
9. Bohlen, M.H., Jensen, C.S., Snodgrass, R.T.: Temporal statement modifiers. TODS, 25(4), (2000)
10. Chatziantoniou, D., Akinde, M.O., Johnson, T., Kim, S.: The md-join: an operator for complex olap. In: ICDE, pp. 524-533 (2001)
11. Chazelle B. (1988). A functional approach to data structures and its use in multidimensional searching. SIAM J. Comput. 17(3): 427-462
12. Chun, S.-J., Chung, C.-W., Lee, J.-H., Lee, S.-L.: Dynamic update cube for range-sum queries, pp. 521-530 (2001)
13. Geffner, S., Agrawal, D., Abbadi, A.E., Smith, T.R.: Relative prefix sums: an efficient approach for querying dynamic olap data cubes. In: ICDE, pp. 328-335 (1999)
14. Gendrano, J.A.G., Huang, B.C., Rodrigue, J.M., Moon, B., Snodgrass, R.T.: Parallel algorithms for computing temporal aggregates. In: ICDE, pp. 418-427 (1999)
15. Govindarajan, S., Agarwal, P.K., Arge, L.: CRB-tree: an efficient indexing scheme for range-aggregate queries. In: ICDT, pp. 143-157 (2003)
16. Greenwald, M., Khanna, S.: Space-efficient online computation of quantile summaries. In: SIGMOD, pp. 58-66 (2001)
17. Guttman, A.: R-trees: a dynamic index structure for spatial searching. In: SIGMOD, pp. 47-57 (1984)
18. Ho, C.-T., Agrawal, R., Megiddo, N., Srikant, R.: Range queries in olap data cubes. In: SIGMOD, pp. 73-88 (1997)
19. Jermaine, C., Pol, A., Arumugam, S.: Online maintenance of very large random samples. In: SIGMOD, pp. 299-310 (2004)
20. Jin, J., An, N., Sivasubramaniam, A.: Analyzing range queries on spatial data. In: ICDE, pp. 525-534 (2000)
21. Kim J.S., Kang S.T. and Kim M.H. (1999). On temporal aggregate processing based on time points. Inform. Process. Lett. (IPL) 71(5-6): 213-220
22. Kline, N., Snodgrass, R.T.: Computing temporal aggregates. In: ICDE, pp. 222-231 (1995)
23. Lazaridis, I., Mehrotra, S.: Progressive approximate aggregate queries with a multi-resolution tree structure. In: SIGMOD, pp. 401-412 (2001)
24. Lin, X., Lu, H., Xu, J., Yu, J.X.: Continuously maintaining quantile summaries of the most recent n elements over a data stream. In: ICDE, pp. 362-374 (2004)
25. Lin X., Xu J., Zhang Q., Lu H., Yu J.X., Zhou X. and Yuan Y. (2006). Approximate processing of massive continuous quantile queries over high-speed data streams. TKDE 18(5): 683-698
26. Lopez I.F.V., Snograss R. and Moon B. (2005). Spatiotemporal aggregate computation: a survey. IEEE Trans. Knowl. Data Eng. 17(2): 271-286
27. Moon B., Lopez I.F.V. and Immanuel V. (2003). Efficient algorithms for large-scale temporal aggregation. TKDE 15(3): 744-759
28. Papadias, D., Kalnis P., Zhang, J., Tao, Y.: Efficient olap operations in spatial data warehouses. In: SSTD, pp. 443-459 (2001)
29. Riedewald, M., Agrawal, D., Abbadi, A.E.: Efficient integration and aggregation of historical information. In SIGMOD, pp. 13-24 (2002)
30. Salzberg B. and Tsotras V.J. (1999). Comparison of access methods for time-evolving data. ACM Comput. Surv. 31(2): 158-221
31. Sun, C., Agrawal, D., Abbadi, A.E.: Exploring spatial datasets with histograms. In: ICDE, pp. 93-102 (2002)
32. Tao, Y., Papadias, D., Faloutsos, C.: Approximate temporal aggregation. In: ICDE, pp. 190-201 (2004)
33. Tao, Y., Papadias, D., Zhang, J.: Aggregate processing of planar points. In: EDBT, pp. 682-700 (2002)
34. Varman P.J. and Verma R.M. (1997). An efficient multiversion access structure. TKDE 9(3): 391-409
35. Yang J. and Widom J. (2003). Incremental computation and maintenance of temporal aggregates. VLDB J. 12(3): 262-283
36. Ye, X., Keane, J.A.: Processing temporal aggregates in parallel. In: International. Conference on Systems, Man, and Cybernetics, pp. 1373-1378 (1997)
37. Zhang, D., Gunopulos, D., Tsotras, V.J., Seeger, B.: Temporal aggregation over data streams using multiple granularities. In: EDBT, pp. 646-663 (2002)
38. Zhang, D., Markowetz, A., Tsotras, V.J., Gunopulos, D., Seeger, B.: Efficient computation of temporal aggregates with range predicates. In: PODS (2001)
39. Zhang D. and Tsotras V.J. (2005). Optimizing spatial min/max aggregations. VLDB J. 14(2): 170-181
40. Zhang, D., Tsotras, V.J., Gunopulos, D.: Efficient aggregation over objects with extent. In: PODS, pp. 121-132 (2002)