Véronique Van Vlasselaer
Véronique Van Vlasselaer
Verified email at kuleuven.be - Homepage
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Year
APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions
V Van Vlasselaer, C Bravo, O Caelen, T Eliassi-Rad, L Akoglu, M Snoeck, ...
Decision Support Systems 75, 38-48, 2015
2022015
Fraud analytics using descriptive, predictive, and social network techniques: a guide to data science for fraud detection
B Baesens, V Van Vlasselaer, W Verbeke
John Wiley & Sons, 2015
1422015
Gotcha! Network-based fraud detection for social security fraud
V Van Vlasselaer, T Eliassi-Rad, L Akoglu, M Snoeck, B Baesens
Management Science 63 (9), 3090-3110, 2017
742017
Determining the use of data quality metadata (DQM) for decision making purposes and its impact on decision outcomes—An exploratory study
HT Moges, V Van Vlasselaer, W Lemahieu, B Baesens
Decision Support Systems 83, 32-46, 2016
252016
Using social network knowledge for detecting spider constructions in social security fraud
V Van Vlasselaer, J Meskens, D Van Dromme, B Baesens
2013 IEEE/ACM International Conference on Advances in Social Networks …, 2013
172013
Guilt-by-constellation: Fraud detection by suspicious clique memberships
V Van Vlasselaer, L Akoglu, T Eliassi-Rad, M Snoeck, B Baesens
2015 48th Hawaii International Conference on System Sciences, 918-927, 2015
152015
Afraid: fraud detection via active inference in time-evolving social networks
V Van Vlasselaer, T Eliassi-Rad, L Akoglu, M Snoeck, B Baesens
Proceedings of the 2015 IEEE/ACM International Conference on Advances in …, 2015
132015
Let's talk 3-CD3
L Jones
Cambridge University, 2005
82005
Social network analysis for fraud detection
B Baesens, V Van Vlasselaer, W Verbeke
Fraud Analytics: Using Descriptive, Predictive, and Social Network …, 2015
52015
A models comparison to estimate commuting trips based on mobile phone data
CAR Pinheiro, V Van Vlasselaer, B Baesens, AG Evsukoff, MAHB Silva, ...
Software Engineering in Intelligent Systems, 35-44, 2015
32015
Predictive analytics for fraud detection
B Baesens, VV Vlasselaer, W Verbeke
Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques …, 0
2
Talent Identification and Status: Using Data Mining to Understand Talent Hierarchies in Teams
S Nijs, N Dries, V Van Vlasselaer, L Sels
Academy of Management Proceedings 2018 (1), 10747, 2018
2018
Advanced Rule-based Learning: Active Learning, Rule Extraction, and Incorporating Domain Knowledge
T Verbraken, V Van Vlasselaer, W Verbeke, D Martens, B Baesens
Advanced Database Marketing, 167-186, 2016
2016
Effects of community-based churn detection in the telecom sector
M Oskarsdottir, J Vanthienen, B Baesens, V Van Vlasselaer, A Backiel
European Conference on Operational Research, Date: 2015/07/12-2015/07/15 …, 2015
2015
FAIR: Forecasting and network analytics for collection risk management.
V Van Vlasselaer
2015
Finding cliques in large fraudulent networks: theory and insights
V Van Vlasselaer, L Akoglu, T Eliassi-Rad, M Snoeck, B Baesens
Conference of the International Federation of Operational Research Societies …, 2014
2014
Gotch’all! Advanced network analysis for detecting groups of fraud
V Van Vlasselaer, L Akoglu, T Eliassi-Rad, M Snoeck, B Baesens
PAW (Predictive Analytics World), Date: 2014/10/29-2014/10/30, Location …, 2014
2014
Social network analytics for fraud detection: insights and challenges
B Baesens, V Van Vlasselaer
SAS Analytics, Date: 2013/10/21-2013/10/22, Location: Orlando, Florida (US), 2013
2013
Improving fraud detection techniques using social network analytics for the Belgian government
V Van Vlasselaer, B Baesens
PAW (Predictive Analytics World), Date: 2013/10/23-2013/10/24, Location …, 2013
2013
Social network analysis for detecting spider constructions in social security fraud: new insights and challenges
V Van Vlasselaer, D Van Dromme, B Baesens
European Conference on Operational Research, Date: 2013/07/01-2013/07/04 …, 2013
2013
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