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Proceedings Paper

Data mining of large astronomical databases with neural tools
Author(s): Giuseppe Longo; Ciro Donalek; Giancarlo Raiconi; A. Staiano; Roberto Tagliaferri; Salvatore Sessa; Fabio Pasian; Riccardo Smareglia; Alfredo Volpicelli
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Paper Abstract

The International Virtual Observatory will pose unprecedented problems to data mining. We shortly discuss the effectiveness of neural networks as aids to the decisional process of the astronomer, and present the AstroMining Package. This package was written in Matlab and C++ and provides an user friendly interactive platform for various data mining tasks. Two applications are also shortly outlined: the derivation of photometric redshifts for a subsample of objects extracted from the Sloan Digital Sky Survey Early Data Release, and the evaluation of systematic patterns in the telemetry data for the Telescopio Nazionale Galilo (TNG).

Paper Details

Date Published: 19 December 2002
PDF: 12 pages
Proc. SPIE 4847, Astronomical Data Analysis II, (19 December 2002); doi: 10.1117/12.461147
Show Author Affiliations
Giuseppe Longo, Univ. Federico II and INAF-Osservatorio Astronomico di Capodimonte (Italy)
Ciro Donalek, Univ. Federico II and INAF-Osservatorio Astronomico di Capodimonte (Italy)
Giancarlo Raiconi, Univ. of Salerno (Italy)
A. Staiano, Univ. of Salerno (Italy)
Roberto Tagliaferri, Univ. of Salerno and INFM (Italy)
Salvatore Sessa, Univ. Federico II (Italy)
Fabio Pasian, INAF-Osservatorio Astronomico di Trieste (Italy)
Riccardo Smareglia, INAF-Osservatorio Astronomico di Trieste (Italy)
Alfredo Volpicelli, Univ. of Salerno (Italy)


Published in SPIE Proceedings Vol. 4847:
Astronomical Data Analysis II
Jean-Luc Starck; Fionn D. Murtagh, Editor(s)

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