一种发现空间共位模式的方法

Fadi Deeb, L. Niepel
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引用次数: 2

摘要

空间共定位模式表示事件(服务/功能)的子集,其实例经常位于一个地理空间中。由于空间事件的实例嵌入在连续空间中并共享各种空间关系,因此共定位模式的发现带来了挑战。在本文中,我们基于以前的一些方法、使用的概念以及它们的一些局限性进行了研究。我们提出了一种克服其他方法缺点的方法。该方法基于空间访问方法(KD-tree)及其基本操作和先验生成算法。实验结果表明了该方法的正确性和完整性。结果还说明了输入数据对性能的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A methodology for discovering spatial co-location patterns
Spatial co-location patterns represent the subsets of events (services/features) whose instances are frequently located together in a geographic space. The co-location patterns discovery presents challenges since the instances of spatial events are embedded in a continuous space and share a variety of spatial relationships. In this paper, we provide a study based on some previous approaches, the concepts that were used, and some of their limitations. We propose a methodology which overcomes the shortcomings of some other approaches. This methodology is based on a spatial access method (KD-tree) with its basic operations and the apriori generation algorithm. The results of conducted experimentation show the correctness and completeness of our approach. The results also illustrate the effect of input data on the performance.
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