首页> 外文会议>European Conference on Principle and Practice of Knowledge Discovery in Databases; 20070917-21; Warsaw(PL) >Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach
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Discovering Emerging Patterns in Spatial Databases: A Multi-relational Approach

机译:在空间数据库中发现新兴模式:一种多关系方法

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Spatial Data Mining (SDM) has great potential in supporting public policy and in underpinning society functioning. One task in SDM is the discovery of characterization and peculiarities of communities sharing socio-economic aspects in order to identify potentialities, needs and public intervention. Emerging patterns (Eps) are a special kind of pattern which contrast two classes. In this paper, we face the problem of extracting Eps from spatial data. At this aim, we resort to a multirelational approach in order to deal with the degree of complexity of discovering Eps from spatial data (i.e., (ⅰ) the spatial dimension implicitly defines spatial properties and relations, (ⅱ) spatial phenomena are affected by autocorrelation). Experiments on real datasets are described.
机译:空间数据挖掘(SDM)在支持公共政策和支持社会功能方面具有巨大潜力。 SDM的一项任务是发现共享社会经济因素的社区的特征和特点,以便确定潜力,需求和公众干预。新兴模式(Eps)是一种特殊的模式,可将两个类别进行对比。在本文中,我们面临着从空间数据中提取Eps的问题。为此,我们采取一种多关系方法来处理从空间数据中发现Eps的复杂程度(即(ⅰ)空间维度隐式定义了空间属性和关系,(ⅱ)空间现象受自相关影响)。描述了对真实数据集的实验。

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