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Titlebook: Advances in Spatial Databases; 6th International Sy Ralf Hartmut Güting,Dimitris Papadias,Fred Lochovs Conference proceedings 1999 Springer

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樓主: Kennedy
31#
發(fā)表于 2025-3-27 00:18:35 | 只看該作者
32#
發(fā)表于 2025-3-27 04:23:34 | 只看該作者
Dynamic Spatial Clustering for Intelligent Mobile Information Sharing and Disseminationollaborating on a common mission and with interests in a common situation domain. A mobile user operating in the field changes location, consumes resources, investigates situations “on the horizon,” and performs other incrementally evolving activities. A mobile user’s information needs are therefore
33#
發(fā)表于 2025-3-27 08:01:01 | 只看該作者
34#
發(fā)表于 2025-3-27 12:35:08 | 只看該作者
35#
發(fā)表于 2025-3-27 14:24:31 | 只看該作者
Efficiently Matching Proximity Relationships in Spatial Databasesmage analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate a proximity matching problem among clusters and features. The investigation involves proximity relationship measurement between clus
36#
發(fā)表于 2025-3-27 18:10:46 | 只看該作者
3D Shape Histograms for Similarity Search and Classification in Spatial Databases, medical imaging or meteorology. The underlying models have to consider spatial properties such as shape or extension as well as thematic attributes. We introduce 3D shape histograms as an intuitive and powerful similarity model for 3D objects. Particular flexibility is provided by using quadratic
37#
發(fā)表于 2025-3-28 01:25:47 | 只看該作者
Multi-way Spatial Joins Using R-Trees: Methodology and Performance Evaluationlization of the .. Although a generalization of the 2-way R-tree join has recently been studied, it did not properly take into account the optimization techniques of the original algorithm. Here, we extend these optimization techniques for M-way joins. Since the join ordering was considered to be im
38#
發(fā)表于 2025-3-28 05:31:51 | 只看該作者
39#
發(fā)表于 2025-3-28 06:31:33 | 只看該作者
Algorithms for Performing Polygonal Map Overlay and Spatial Join on Massive Data Setsputational geometry to solve these problems for massive data sets. A performance study with artificial and real-world data sets helps to identify the algorithm that should be used for given input data.
40#
發(fā)表于 2025-3-28 11:56:23 | 只看該作者
A Performance Evaluation of Spatial Join Processing Strategiess and use a common set of spatial joins algorithms, among which one is a novel extension of a strategy based on an on-the-fly index creation prior to the join with another indexed relation. A common platform is used on which a set of spatial access methods and join algorithms are available. The QEPs
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