空间数据挖掘在从大型空间数据集中发现有趣的和以前未知的但可能有用的模式过程中的应用

Abinash Das
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引用次数: 0

摘要

空间数据挖掘通常用于地理信息系统,从物理数据集和位置到现实世界的事件。资本数据挖掘中常用的一种方法是向量数据表示。矢量数据是世界上最常用的数据。这种格式的信息由尖端、角度和四边形组成。这是分析数据的最简单方法,其中矢量数据由提示相关对组成,以指示世界中的物理位置。这些点可以以一种特殊的方式连接起来,形成标记为四边形的封闭区域。矢量数据对于存储和表示具有离散边界(如国际边界、街道、建筑物等)的数据非常有用。谷歌等现代技术使用地质信息和开放街道地图以矢量数据结构的方式表示数据。关键词:空间数据挖掘,矢量数据,信息系统,安全,数据
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Spatial Data Mining in the Process of Discovering Interesting and Previously Unknown, but Potentially Useful, Patterns from Large Spatial Datasets
Spatial data mining has been typically used in the Geographical Information system from physical datasets and locations to real-world events. One of the procedures generally used in capital data mining is vector data representation. Vector data is the most commonly used data across the world. Information in this format consists of tips, angles, and quadrilaterals. It is the simplest method of analysing the data where the vector data consists of tips correlate pairs to indicate a physical location in the world. These points can be joined in a particular way to form closed areas marked as quadrilaterals. Vector data is extremely useful for storing and representing data that has discrete boundaries such as international borders, streets, buildings, and many more. Modern technologies such as Google use geological information and open street maps to represent the data in vector data stricture wise. Keyword : Spatial data mining, Vector data, Information system, Security, Data
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