Improved histograms for selectivity estimation of range predicates
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Selectivity estimation in spatial databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Designing and mining multi-terabyte astronomy archives: the Sloan Digital Sky Survey
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Dynamic Update Cube for Range-sum Queries
Proceedings of the 27th International Conference on Very Large Data Bases
LATIN '98 Proceedings of the Third Latin American Symposium on Theoretical Informatics
Efficient OLAP Operations in Spatial Data Warehouses
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Accurate Estimation of the Cost of Spatial Selections
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Analyzing Range Queries on Spatial Data
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Exploring Spatial Datasets with Histograms
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Multiscale histograms: summarizing topological relations in large spatial datasets
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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Summarizing topological relations is fundamental to many spatial applications including spatial query optimization. In this paper, we examine the selectivity estimation for range window query to summarize the four important topological relations: contains, contained, overlap, and disjoint. We propose a novel hybrid histogram method which uses the concept of Min-skew partition in conjunction with Euler histogram approach. It can effectively model object spatial distribution. Our extensive experiments against both synthetic and real world datasets demonstrated that our hybrid histogram techniques improve the accuracy of the existing techniques by about one order of magnitude while retaining the cost efficiency.