Publication at Faculty of Mathematics and Physics |
2019
Abstract
In our ongoing project focusing primarily on bank clients, we propose an innovative strategy that will overcome shortcomings of the existing methods. From a given set of user activities, we infer their social network in order to analyze user relationships and behavior.
For this purpose, not just the traditional direct facts are incorporated, but also relationships inferred using similarity measures and statistical approaches, with both possibly limited measures of reliability and validity in time. Such networks would enable analyses of client characteristics from a new perspective and could provide otherwise impossible insights.