Probabilistic counting algorithms for data base applications
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The R*-tree: an efficient and robust access method for points and rectangles
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Adaptive selectivity estimation using query feedback
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Indexing the positions of continuously moving objects
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Efficient computation of temporal aggregates with range predicates
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Progressive approximate aggregate queries with a multi-resolution tree structure
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Efficient aggregation over objects with extent
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Dynamic multidimensional histograms
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R-trees: a dynamic index structure for spatial searching
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Aggregate Processing of Planar Points
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CRB-Tree: An Efficient Indexing Scheme for Range-Aggregate Queries
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Overcoming Limitations of Sampling for Aggregation Queries
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The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
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Efficient OLAP Operations in Spatial Data Warehouses
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Sequenced spatiotemporal aggregation for coarse query granularities
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PNN query processing on compressed trajectories
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Spatio-temporal aggregations in trajectory data warehouses
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Materialized views for count aggregates of spatial data
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A new spatio-temporal prediction approach based on aggregate queries
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Several spatio-temporal applications require the retrievalof summarized information about moving objects that liein a query region during a query interval (e.g., the numberof mobile users covered by a cell, traffic volume in adistrict, etc.). Existing solutions have the distinct countingproblem: if an object remains in the query region forseveral timestamps during the query interval, it will becounted multiple times in the result. The paper solves thisproblem by integrating spatio-temporal indexes withsketches, traditionally used for approximate queryprocessing. The proposed techniques can also be appliedto reduce the space requirements of conventional spatio-temporaldata and to mine spatio-temporal association rules.