| 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 | 445 | 2015 |
| 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 | 278 | 2015 |
| 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 | 158 | 2017 |
| 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 | 38 | 2016 |
| Using social network knowledge for detecting spider constructions in social security fraud V Van Vlasselaer, J Meskens, D Van Dromme, B Baesens Proceedings of the 2013 IEEE/ACM International Conference on Advances in …, 2013 | 25 | 2013 |
| 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 | 20 | 2015 |
| 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 | 19 | 2015 |
| Reframing talent identification as a status‐organising process: Examining talent hierarchies through data mining S Nijs, N Dries, V Van Vlasselaer, L Sels Human Resource Management Journal 32 (1), 169-193, 2022 | 11 | 2022 |
| Social network analysis for fraud detection B Baesens, V Van Vlasselaer, W Verbeke Fraud Analytics: Using Descriptive, Predictive, and Social Network …, 2015 | 6 | 2015 |
| Fraud: Detection, Prevention, and Analytics B Baesens, VV Vlasselaer, W Verbeke Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques …, 2015 | 5 | 2015 |
| The Quest for AI: A History of Ideas and Achievements NJ Nilsson, Y Hilpisch, M Yao, A Zhou, M Jia, B Baesen, V Van Vlasselaer, ... Erişim adresi: http://ai. standford. edu/~ nilsson/(Özgün eser 2009 tarihlidir), 2010 | 5 | 2010 |
| 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: Proceedings of the 4th Computer …, 2015 | 3 | 2015 |
| 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 | 1 | 2018 |
| 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 | 1 | 2014 |
| 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 |
| An Economic Perspective on Fraud Analytics: Calculating ROI of Fraud Detection Systems B Baesens, V Van Vlasselaer, W Verbeke | | 2015 |
| Building multi-armed fraud detection systems using descriptive, predictive and social network analytics B Baesens, V Van Vlasselaer, W Verbeke | | 2015 |
| Networks vs. Fraud: Connecting the dots B Baesens, V Van Vlasselaer, W Verbeke | | 2015 |
| 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 |
