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Due to the complexity of geoscientific data, such as geochemical data, geophysical data and digital remote sensing data, traditional data mining methods, such as cluster analysis and association analysis, have limitations in resources evaluation. In this paper, a clustering algorithm is presented which has the ability to handle clusters of arbitrary shapes, sizes and densities. For association analysis,...
For applications of data mining techniques in geosciences, through mining spatial databases which are constructed with geophysical and geochemical data measured in fields, the knowledge, such as the spatial distribution of geological targets, the geophysical and geochemical characteristics of geological targets, the differentiation among the geological targets, and the relationship among geophysical...
In association analysis, mining the continuous attributes may reveal useful and interesting insights about the data objects which are of continuous attributes. Quantitative association rules are aimed to deal with the relationships among continuous attributes of data objects. This paper presents an association analysis algorithm based on the distances among clusters. The algorithm uses a clustering...
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