A paper on Building Client’s Risk Profile Based on Call Detail Records by Z. Herga, C. Doyle, S. Dipple, C. Nasman, G. Korniss, B.K. Szymanski, J. Brank, J. Rupnik, and D. Mladenic has been published in Proc SiKDD, Oct. 8, 2017.

A paper titled "Building Client’s Risk Profile Based on Call Detail Records" by Data collected from mobile phones can be used to uncover underlying social network dynamics and individual's behavioral patterns. Based on a Call Details Records dataset, we build a weighted, directed network and analyze it's properties. In addition to node-level network measures we extract an extensive consumption and mobility-based feature set. We show that extracted network and consumption features can be used to model individual's risk profile. Zala Herga, Casey Doyle, Stephen Dipple, Caleb Nasman, Gyorgy Korniss, Boleslaw Szymanski, Janez Brank, Jan Rupnik, and Dunja Mladenic was published in Proc. Conference on Data Mining and Data Warehouses (SiKDD), October 9th, 2017, Ljubljana, Slovenia, pp. 1-4. The paper resulted from collaboration in EU Renoir Project and is available via the link below. Data collected from mobile phones can be used to uncover underlying social network dynamics and individual's behavioral patterns. Based on a Call Details Records dataset, we build a weighted, directed network and analyze it's properties. In addition to node-level network measures we extract an extensive consumption and mobility-based feature set. We show that extracted network and consumption features can be used to model individual's risk profile.