A Data Mining framework to model Consumer Indebtedness with Psychological Factors
February 20, 2015 ยท Declared Dead ยท ๐ 2014 IEEE International Conference on Data Mining Workshop
"No code URL or promise found in abstract"
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Authors
Alexandros Ladas, Eamonn Ferguson, Uwe Aickelin, Jon Garibaldi
arXiv ID
1502.05911
Category
cs.LG: Machine Learning
Cross-listed
cs.CE
Citations
10
Venue
2014 IEEE International Conference on Data Mining Workshop
Last Checked
3 months ago
Abstract
Modelling Consumer Indebtedness has proven to be a problem of complex nature. In this work we utilise Data Mining techniques and methods to explore the multifaceted aspect of Consumer Indebtedness by examining the contribution of Psychological Factors, like Impulsivity to the analysis of Consumer Debt. Our results confirm the beneficial impact of Psychological Factors in modelling Consumer Indebtedness and suggest a new approach in analysing Consumer Debt, that would take into consideration more Psychological characteristics of consumers and adopt techniques and practices from Data Mining.
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