Title :
Classifying bent-double galaxies
Author :
Kamath, Chandrika ; Cantu-Paz, E. ; Fodor, Imola K. ; Tang, Nu Ai
Author_Institution :
Center for Appl. Sci. Comput., Lawrence Livermore Nat. Lab., CA, USA
Abstract :
Astronomy data sets have led to interesting problems in mining scientific data. These problems will likely become more challenging as the astronomy community brings several surveys online as part of the National Virtual Observatory, giving rise to the possibility of mining data across many different surveys. In this article, we discuss the work we performed while using the catalog from the FIRST (Faint Images of the Radio Sky at Twenty centimetres) survey to classify galaxies with a bent-double morphology, meaning those galaxies that appear to be bent in shape. We describe the approach we took to mine this data, the issues we addressed in working with a real data set, and the lessons we learned in the process
Keywords :
astronomy computing; classification; data mining; galaxies; FIRST survey; National Virtual Observatory; astronomy computing; astronomy data sets; bent-double galaxies; data mining; galaxy classification; scientific data; Astronomy; Catalogs; Classification tree analysis; Data mining; Decision trees; Morphology; Neural networks; Observatories; Telescopes; Volcanoes;
Journal_Title :
Computing in Science & Engineering
DOI :
10.1109/MCISE.2002.1014980