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Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract)

  • Luc De Raedt
  • Siegfried Nijssen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6804)

Abstract

Today there is only little support for developing software that incorporates a machine learning or a data mining component. To alleviate this situation, we propose to develop programming languages for machine learning and data mining. We also argue that such languages should be declarative and should be based on constraint programming modeling principles. In this way, one could declaratively specify the problem of machine learning or data mining problem of interest in a high-level modeling language and then translate it into a constraint satisfaction or optimization problem, which could then be solved using particular solvers. These ideas are illustrated on problems of constraint-based itemset and pattern set mining.

Keywords

Data Mining Constraint Satisfaction Pattern Mining Constraint Satisfaction Problem Inductive Logic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Luc De Raedt
    • 1
  • Siegfried Nijssen
    • 1
  1. 1.Department of Computer ScienceKatholieke Universiteit LeuvenBelgium

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