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首页> 外文会议>International Conference on Conceptual Modeling(ER 2004): Workshops on CoMoGIS, CoMWIM, ECDM, CoMoA, DGOV, and eCOMO; 20041108-12; Shanghai(CN) >A Scaleless Data Model for Direct and Progressive Spatial Query Processing
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A Scaleless Data Model for Direct and Progressive Spatial Query Processing

机译：直接和渐进式空间查询处理的无标度数据模型

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摘要

A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.
机译：渐进式空间查询基于先前的查询来检索空间数据（例如，以更高分辨率在更受限的区域中获取数据）。另一方面，直接查询被定义为隔离的窗口查询。多分辨率空间数据库系统应支持渐进式查询和传统直接查询。同时支持两种类型的查询在概念上具有挑战性，因为直接查询有利于基于位置的数据聚类，而渐进式查询则需要通过分辨率将零散的数据聚类。本文提出了两种新的无标度数据结构。使用合成数据集和现实世界数据集的实验结果表明，对于两种类型的查询，基于新的多分辨率方法的查询处理时间都是可比的，并且通常比多表示数据结构更好。

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