迈向虚拟天文台的分类器。I.分类SDSS光度学档案
Steps toward a classifier for the Virtual Observatory. I. Classifying the SDSS photometric archive
摘要：
现代测光多波段数字测量产生大量数据，为了有效利用这些数据，需要能够从测光数据中提取客观分类的自动工具。在这里，我们提出了一种新的方法，在大型多参数光度数据库中的对象进行分类，由一个聚类算法和集群凝聚工具的组合。的泛化能力和这种方法的潜力进行了测试，对斯隆数字巡天档案的复杂性，其中一个应用程序的例子报告。
英文摘要：
Modern photometric multiband digital surveys produce large amounts of data that, in order to be effectively exploited, need automatic tools capable to extract from photometric data an objective classification. We present here a new method for classifying objects in large multi-parametric photometric data bases, consisting of a combination of a clustering algorithm and a cluster agglomeration tool. The generalization capabilities and the potentialities of this approach are tested against the complexity of the Sloan Digital Sky Survey archive, for which an example of application is reported.
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