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      • Computing and Mathematical Sciences
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      Scientific workflow management with ADAMS

      Reutemann, Peter; Vanschoren, Joaquin
      DOI
       10.1007/978-3-642-33486-3_58
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      Reutemann, P. & Vanschoren, J. (2012). Scientific workflow management with ADAMS. In Lecture Notes in Computer Science, 2012, Volume 7524 LNAI, Issue Part 2: Machine Learning and Knowledge Discovery in Databases,pp. 833-837.
      Permanent Research Commons link: https://hdl.handle.net/10289/6766
      Abstract
      We demonstrate the Advanced Data mining And Machine learning System (ADAMS), a novel workflow engine designed for rapid prototyping and maintenance of complex knowledge workflows. ADAMS does not require the user to manually connect inputs to outputs on a large canvas. It uses a compact workflow representation, control operators, and a simple interface between operators, allowing them to be auto-connected. It contains an extensive library of operators for various types of analysis, and a convenient plug-in architecture to easily add new ones.
      Date
      2012
      Type
      Chapter in Book
      Publisher
      Springer
      Collections
      • Computing and Mathematical Sciences Papers [1454]
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