Title: Country corruption analysis with self organizing maps and support vector machines
Authors: Huysmans, Johan ×
Martens, David
Baesens, Bart
Vanthienen, Jan
Van Gestel, Tony #
Issue Date: 2006
Publisher: Springer
Series Title: Lecture Notes in Computer Science vol:3917 pages:103-114
Conference: Proceedings of the Tenth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Workshop on Intelligence and Security Informatics (WISI), Lecture Notes in Computer Science
Abstract: During recent years, the empirical research on corruption has grown considerably. Possible links between government corruption and terrorism have attracted an increasing interest in this research field. Most of the existing literature discusses the topic from a socio-economical perspective and only few studies tackle this research field from a data mining point of view. In this paper, we apply data mining techniques onto a cross-country database linking macro-economical variables to perceived levels of corruption. In the first part, self organizing maps are applied to study the interconnections between these variables. Afterwards, support vector machines are trained on part of the data and used to forecast corruption for other countries. Large deviations for specific countries between these models' predictions and the actual values can prove useful for further research. Finally, projection of the forecasts onto a self organizing map allows a detailed comparison between the different models' behavior.
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Management Informatics (LIRIS), Leuven
× corresponding author
# (joint) last author

Files in This Item:
File Status SizeFormat
Country corruption.pdf Submitted 372KbAdobe PDFView/Open


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science