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Subscription fraud prevention in telecommunications using fuzzy rules and neural networks
2 references·12 citing·39 second hop
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References

  • 2002Turning telecommunications call details to churn prediction: a data mining approach460 cited
  • 2000Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry347 cited

Cited by

  • 2010A data mining framework for detecting subscription fraud in telecommunication74 cited
  • 2010Combined rough set theory and flow network graph to predict customer churn in credit card accounts67 cited
  • 2016A knowledge based scheme for risk assessment in loan processing by banks39 cited
  • 2010A Framework for Internal Fraud Risk Reduction at IT Integrating Business Processes, The IFR² Framework31 cited
  • 2009A Framework for Internal Fraud Risk Reduction at IT Integrating Business Processes: The IFR² Framework27 cited
  • 2012Detecting SIM Box Fraud Using Neural Network22 cited
  • 2010User Modeling for Telecommunication Applications: Experiences and Practical Implications21 cited
  • 2008Supervised Classification for Decision Support in Customer Relationship Management19 cited
  • 2009The Application of the Locally Linear Model Tree on Customer Churn Prediction19 cited
  • 2019Prediction of Customer Plan using Churn Analysis for Telecom Industry18 cited
  • 2009A framework for Internal Fraud Risk Reduction at IT Integrating Business Processes12 cited
  • 2013

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Churn Management and Policy: Measuring the Effectiveness of Fixed-Mobile Bundling on Mobile Subscriber Retention
11 cited