Using data-driven and process mining techniques for identifying and characterizing problem gamblers in New Zealand

Simple item page
dc.citation.volume9
dc.contributor.authorSuriadi S
dc.contributor.authorSusnjak T
dc.contributor.authorPonder-Sutton A
dc.contributor.authorWatters P
dc.contributor.authorSchumacher CR
dc.date.available2016-12
dc.date.issued2016-12
dc.description.confidentialfalse
dc.format.extent44 - 66 (23)
dc.identifier.citationComplex Systems Informatics and Modeling Quarterly, 2016, 9 pp. 44 - 66 (23)
dc.identifier.doi10.7250/csimq.2016-9.03
dc.identifier.eissn2255-9922
dc.identifier.elements-id343576
dc.identifier.harvestedMassey_Dark
dc.publisherRTU Press
dc.relation.isPartOfComplex Systems Informatics and Modeling Quarterly
dc.rights2016 Suriadi et al. This is an open access article licensed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0).
dc.subject.anzsrc0102 Applied Mathematics
dc.subject.anzsrc0104 Statistics
dc.titleUsing data-driven and process mining techniques for identifying and characterizing problem gamblers in New Zealand
dc.typeJournal article
pubs.notesNot known
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/College of Sciences
pubs.organisational-group/Massey University/Massey Business School
pubs.organisational-group/Massey University/Massey Business School/School of Economics and Finance
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
CSIMQ article.pdf
Size:
3.47 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Journal Articles