Research and application of cluster and association analysis in geochemical data processing |
| |
| Authors: | Hai-Dong Meng Yu-Chen Song Fei-Yan Song Hai-Tao Shen |
| |
| Institution: | (1) The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 100190 Beijing, China;(2) Graduate University of Chinese Academy of Sciences, 100039 Beijing, China |
| |
| Abstract: | For applications of data mining techniques in geosciences, through mining spatial databases which are constructed with geophysical
and geochemical data measured in fields, critical 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 and geochemical data, can be discovered. Due to the complexity of geophysical and geochemical data, traditional
mining methods of cluster analysis and association analysis have limitations in processing complex data. In this paper, a
clustering algorithm based on density and adaptive density-reachable is presented which has the ability to handle clusters
of arbitrary shapes, sizes, and densities. For association analysis, mining the continuous attributes may reveal useful and
interesting insights about the data objects in geoscientific applications. An approach for distance-based quantitative association
analysis is presented in this paper. Experiments and applications indicate that the algorithm and approach are effective in
real-world applications. |
| |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ |
|
