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Using clustering to extract personality information from socio economic data

Ladas, Alexandros; Aickelin, Uwe; Garibaldi, Jonathan M.; Ferguson, Eamonn

Authors

Alexandros Ladas

Uwe Aickelin uwe.aickelin@nottingham.ac.uk

Jonathan M. Garibaldi jmg@cs.nott.ac.uk

Eamonn Ferguson



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.

Peer Reviewed Peer Reviewed
APA6 Citation Ladas, A., Aickelin, U., Garibaldi, J. M., & Ferguson, E. Using clustering to extract personality information from socio economic data
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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Using_Clustering_to_extract_Personality_Information_from_socio_economic_data.UKCI_2012.2012.pdf (510 Kb)
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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