Alexandros Ladas
Using clustering to extract personality information from socio economic data
Ladas, Alexandros; Aickelin, Uwe; Garibaldi, Jonathan M.; Ferguson, Eamonn
Authors
Uwe Aickelin
Jonathan M. Garibaldi
EAMONN FERGUSON eamonn.ferguson@nottingham.ac.uk
Professor of Health Psychology
Abstract
It has become apparent that models that have been applied widely in economics, including Machine Learning techniques and Data Mining methods, should take into consideration principles that derive from the theories of Personality Psychology in order to discover more comprehensive knowledge regarding complicated economic behaviours. In this work, we present a method to extract Behavioural Groups by using simple clustering techniques that can potentially reveal aspects of the Personalities for their members. We believe that this is very important because the psychological information regarding the Personalities of individuals is limited in real world applications and because it can become a useful tool in improving the traditional models of Knowledge Economy.
Citation
Ladas, A., Aickelin, U., Garibaldi, J. M., & Ferguson, E. Using clustering to extract personality information from socio economic data.
Conference Name | 12th UK Workshop on Computational Intelligence (UKCI 2012) |
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End Date | Sep 7, 2012 |
Deposit Date | Jul 18, 2013 |
Peer Reviewed | Peer Reviewed |
Public URL | https://nottingham-repository.worktribe.com/output/1008842 |
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Using_Clustering_to_extract_Personality_Information_from_socio_economic_data.UKCI_2012.2012.pdf
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