Astronomy and Astrophysics – Astrophysics
Scientific paper
2000-11-30
Astronomy and Astrophysics
Astrophysics
7 pages, 7 figures, 1 table, to appear in proceedings of the MPA/MPE/ESO joint conference "Mining the Sky" held in Garching, G
Scientific paper
10.1007/10849171_63
Gamma-ray bursts provide what is probably one of the messiest of all astrophysical data sets. Burst class properties are indistinct, as overlapping characteristics of individual bursts are convolved with effects of instrumental and sampling biases. Despite these complexities, data mining techniques have allowed new insights to be made about gamma-ray burst data. We demonstrate how data mining techniques have simultaneously allowed us to learn about gamma-ray burst detectors and data collection, cosmological effects in burst data, and properties of burst subclasses. We discuss the exciting future of this field, and the web-based tool we are developing (with support from the NASA AISR Program). We invite others to join us in AI-guided gamma-ray burst classification (http://grb.mnsu.edu/grb/).
Haglin David J.
Hakkila Jon
Mallozzi Robert S.
Meegan Charles A.
Pendleton Geoffrey N.
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