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DAME: A Web Oriented Infrastructure for Scientific Data Mining & Exploration (1010.4843v2)

Published 23 Oct 2010 in astro-ph.IM, astro-ph.GA, cs.DB, cs.DC, and cs.SE

Abstract: Nowadays, many scientific areas share the same need of being able to deal with massive and distributed datasets and to perform on them complex knowledge extraction tasks. This simple consideration is behind the international efforts to build virtual organizations such as, for instance, the Virtual Observatory (VObs). DAME (DAta Mining & Exploration) is an innovative, general purpose, Web-based, VObs compliant, distributed data mining infrastructure specialized in Massive Data Sets exploration with machine learning methods. Initially fine tuned to deal with astronomical data only, DAME has evolved in a general purpose platform which has found applications also in other domains of human endeavor. We present the products and a short outline of a science case, together with a detailed description of main features available in the beta release of the web application now released.

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Authors (15)
  1. Massimo Brescia (63 papers)
  2. Giuseppe Longo (75 papers)
  3. George S. Djorgovski (3 papers)
  4. Stefano Cavuoti (57 papers)
  5. Raffaele D'Abrusco (33 papers)
  6. Ciro Donalek (19 papers)
  7. Alessandro Di Guido (2 papers)
  8. Michelangelo Fiore (4 papers)
  9. Mauro Garofalo (7 papers)
  10. Omar Laurino (9 papers)
  11. Ashish Mahabal (73 papers)
  12. Francesco Manna (3 papers)
  13. Alfonso Nocella (3 papers)
  14. Giovanni d'Angelo (2 papers)
  15. Maurizio Paolillo (71 papers)
Citations (9)

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