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Bibliography
Journal articles
Accepted Journal articles
Mitrovic S., Baesens B., Lemahieu W., De Weerdt J. (2018). On the operational efficiency of different feature types for telco churn prediction. European Journal of Operational Research.
Conference Proceedings
Accepted Conference Proceedings
Mitrovic S., Singh G., Baesens B., Lemahieu W., De Weerdt J. (2017). Scalable rfm-enriched representation learning for churn prediction. In: Proceedings of the fourth IEEE International Conference on Data Science and Advanced Analytics (DSAA2017) Presented at the IEEE International Conference on Data Science and Advanced Analytics (DSAA2017), Tokyo (Japan), 19 Oct 2017-21 Oct 2017.
Mitrovic S., Baesens B., Lemahieu W., De Weerdt J. (2017). Churn prediction using dynamic rfm-augmented node2vec. In: Proceedings of the Third international workshop on Dynamics in and of Networks, ECML-PKDD 2017 Presented at the International workshop on Dynamics in and of Networks, ECML-PKDD 2017, Skopje (Macedonia), 18 Sep 2017-22 Sep 2017.
Abstracts/Presentations/Posters
Van Calster T., Reusens M., Oskarsdottir M., Mitrovic S., Lismont J., De Weerdt J., Lemahieu W., Baesens B., Vanthienen J. (2017). What's in the network? A stepwise overview of working with networked data in R. Presented at the useR!, Brussels (Belgium), 05 Jul 2017-07 Jul 2017.
Mitrovic S., Baesens B., Lemahieu W., De Weerdt J. (2017). On added value of feature engineering for churn prediction. Presented at the NetMob 2017, Milan (Italy), 05 Apr 2017-07 Apr 2017.