Using Data-Driven and Process Mining Techniques for Identifying and Characterizing Problem Gamblers in New Zealand

Using Data-Driven and Process Mining Techniques for Identifying and Characterizing Problem Gamblers in New Zealand

This article uses data-driven techniques combined with established theory in order to analyse gambling behavioural patterns of 91 thousand individuals on a real-world fixed-odds gambling dataset in New Zealand. This research uniquely integrates a mixture of process mining, data mining and confirmato...

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Bibliographic Details
Main Authors: Suriadi Suriadi, Teo Susnjak, Agate M. Ponder-Sutton, Paul A. Watters, Christoph Schumacher
Format: Article
Language:English
Published: Riga Technical University 2016-12-01
Series:Complex Systems Informatics and Modeling Quarterly
Subjects:
Data mining
process mining
confirmatory statistics
problem gambling
Online Access:https://csimq-journals.rtu.lv/article/view/1547
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https://csimq-journals.rtu.lv/article/view/1547

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