Joint European Conference on Machine Learning and Knowledge Discovery in Databases

ECML PKDD 2015: Machine Learning and Knowledge Discovery in Databases pp 37-52

Country-Scale Exploratory Analysis of Call Detail Records Through the Lens of Data Grid Models

  • Romain Guigourès
  • Dominique Gay
  • Marc Boullé
  • Fabrice Clérot
  • Fabrice Rossi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)

Abstract

Call Detail Records (CDRs) are data recorded by telecommunications companies, consisting of basic informations related to several dimensions of the calls made through the network: the source, destination, date and time of calls. CDRs data analysis has received much attention in the recent years since it might reveal valuable information about human behavior. It has shown high added value in many application domains like e.g., communities analysis or network planning.

In this paper, we suggest a generic methodology based on data grid models for summarizing information contained in CDRs data. The method is based on a parameter-free estimation of the joint distribution of the variables that describe the calls. We also suggest several well-founded criteria that allows one to browse the summary at various granularities and to explore the summary by means of insightful visualizations. The method handles network graph data, temporal sequence data as well as user mobility data stemming from original CDRs data. We show the relevance of our methodology on real-world CDRs data from Ivory Coast for various case studies, like network planning strategy and yield management pricing strategy.

Keywords

Classification rule Bayes theory Minimum description length 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Romain Guigourès
    • 1
  • Dominique Gay
    • 2
  • Marc Boullé
    • 2
  • Fabrice Clérot
    • 2
  • Fabrice Rossi
    • 3
  1. 1.ZalandoBerlinGermany
  2. 2.Orange Labs LannionLannionFrance
  3. 3.SAMM EA 4543, Univeristé Paris 1ParisFrance

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