Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases

نویسندگان

  • Robert Trappl
  • Johannes Fürnkranz
  • Johann Petrak
چکیده

In the last decade research in Machine Learning has developed a variety of powerful tools for inductive learning and data analysis. On the other hand, research in International Relations has developed a variety of different conflict databases that are mostly analyzed with classical statistical methods. As these databases are in general of a symbolic nature, they provide an interesting domain for application of Machine Learning algorithms. This paper gives a short overview of available conflict databases and subsequently concentrates on the application of machine learning methods for the analysis and interpretation of the CONFMAN mediation dataset.

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تاریخ انتشار 1996