@INPROCEEDINGS{MraZvi14cas,
  author = {Iveta Mrázová and Peter Zvirinský},
  title = {Mining the Czech Insolvency Proceedings Data},
  booktitle = {Proceedings of the Complex Adaptive Systems 2014 Conference -- Conquering
    Complexity: Challenges and Opportunities, Philadelphia, PA, USA,
    November 3--5, 2014},
  year = {2014},
  editor = {Cihan H. Dagli},
  volume = {36},
  series = {Procedia Computer Science},
  pages = {308--313},
  publisher = {Elsevier},
  bibsource = {dblp computer science bibliography, http://dblp.org},
  biburl = {http://dblp.uni-trier.de/rec/bib/conf/complexsystems/MrazovaZ14},
  crossref = {DBLP:conf/complexsystems/2014},
  doi = {10.1016/j.procs.2014.09.098},
  timestamp = {Thu, 27 Nov 2014 19:54:35 +0100},
  url = {http://dx.doi.org/10.1016/j.procs.2014.09.098},
  abstract = {The Global Financial Crisis of 2008 has left behind it many victims worldwide – both among bankrupt companies and indebted people with a grim future ahead. On January 1, 2008, the government of the Czech Republic launched a new information system called Insolvency Register of the Czech Republic. Meanwhile, the Czech Insolvency Register contains publicly available data concerning more than 100 000 insolvency proceedings. Modern data mining methods quite naturally represent an appealing approach to analyze these huge amounts of open source data. In this context, especially the techniques of Bayesian networks and social network analysis seem to reveal several new socio-economic patterns present in the current Czech society.}
}