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Spatial Query Processing for Sketch-Based Query Using Heuristics

机译:基于启发式的基于草图的查询的空间查询处理

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摘要

Sketching the spatial query is one of the leading spatial databases query method (Blaser 2000) for searching similar configuration. However, when the sketched spatial scene is processed with ordinary query processing method, it does not achieve efficiency that is desired especially deals with large datasets (N>1000) as Blaser (2000). Therefore indexing and heuristics are proposed to be able to help in reducing the search space and enhance the search performance (Papadias and Mamoulis 1999) for configuration similarity. The most prominent indexing method of spatial objects is R-Tree. With the indexed spatial objects, then heuristics could be applied to improve the searching efficiency i.e. reducing the searching cost and increasing the number of solutions to query. This paper aims to discuss the generic R-Tree model, then discuss the heuristics that could be applied to utilize the data structure in their searching of configuration similarity in spatial query by sketch.
机译:绘制空间查询草图是用于搜索相似配置的领先空间数据库查询方法(Blaser 2000)之一。但是,当用普通的查询处理方法处理草绘的空间场景时,它无法达到所需的效率,尤其是像Blaser(2000)那样处理大型数据集(N> 1000)时。因此,提出了索引和启发式方法,能够帮助减少搜索空间并提高配置相似性的搜索性能(Papadias和Mamoulis 1999)。空间对象最主要的索引方法是R-Tree。对于索引的空间对象,然后可以使用启发式方法来提高搜索效率,即降低搜索成本并增加要查询的解决方案的数量。本文旨在讨论通用的R-Tree模型,然后讨论可用于在草图中查询空间查询中的结构相似性时利用数据结构的启发式方法。

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