Analysis of Call Detail Records for Understanding Users Behavior and Anomaly Detection Using Neo4j

  • Emsaieb Geepalla
  • Nasser Abuhamoud
  • Abdulla Abouda
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 753)


Call Detail Records (CDR) is a valuable source of information; it opens new opportunities for mobile operator industries and maximize their revenues as well as it helps the community to raise its standard of living in many different ways. Nevertheless, we need to analyze CDR in order to extract its big value and detect abnormal costumers behaviors to help companies to develop their future plans. However the analysis of CDRs is a very complex process this because it has a huge volume of data. Therefore, In this paper we propose an approach that makes use of Neo4j for automatic analysis of CDRs. To achieve this we transformed the CDR data into neo4j and then we used cypher query language for performing an automatic analysis. A real case study was used to evaluate the proposed approach.


Call Detail Records Big data Neo4j Graph database Abnormal user behavior 



This research was supported by the Research & Development (R&D) office at Almadar Aljadid Company. We thank our colleagues from R&D office at Almadar Aljadid Company who provided insight and expertise that greatly assisted the research.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Communication and Computer EngineeringSebha UniversitySebhaLibya
  2. 2.Research and Development Office, Almadar Aljadid Co.TripoliLibya

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