Data Mining Large Astronomical Databases for Interacting Galaxies

Computer Science – Databases

Scientific paper

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Scientific paper

We will present results from an exploratory data mining project to identify classification features of special classes of interacting galaxies (for example, infrared-luminous galaxies) within distributed astronomical databases. Using a variety of data mining techniques, interaction-specific features are learned, to distinguish this class of galaxies from a control sample of normal galaxies. Subsequently, the corresponding rule-based feature model of that class of galaxies is then applied to the large multi-wavelength astronomical databases that are now becoming available. This distributed data mining activity is a prototype science use case for the Virtual Observatory. We specifically apply multi-archive multi-wavelength data to the problem. We will present examples of both successful and unsuccessful data mining attempts.

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