Advanced Behavioral Analyses Using Inferred Social Networks: A Vision

  • Irena Holubová
  • Martin SvobodaEmail author
  • Tomáš Skopal
  • David Bernhauer
  • Ladislav Peška
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1062)


The success of many businesses is based on a thorough knowledge of their clients. There exists a number of supervised as well as unsupervised data mining or other approaches that allow to analyze data about clients, their behavior or environment. 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. However, there are several research and technical challenges making the outlined pursuit novel, complex and challenging as we outline in this vision paper.


Inferred social networks Similarity Behavioral analysis 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Mathematics and PhysicsCharles UniversityPragueCzech Republic
  2. 2.Faculty of Information TechnologyCzech Technical University in PraguePragueCzech Republic

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