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Using data mining for bank direct marketing: an application of the CRISP-DM methodology
2 references·16 citing·47 second hop
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this work references cited by second hop

References

  • 1998Data mining for direct marketing: problems and solutions658 cited
  • 2006Decision Support and Business Intelligence Systems (8th Edition)162 cited

Cited by

  • 2016Customer relationship management mechanisms: A systematic review of the state of the art literature and recommendations for future research228 cited
  • 2018Adaptive Sensitive Reweighting to Mitigate Bias in Fairness-aware Classification127 cited
  • 2015An Efficient CRM-Data Mining Framework for the Prediction of Customer Behaviour118 cited
  • 2014Bank Direct Marketing Analysis of Data Mining Techniques80 cited
  • 2013Concept Drift-Oriented Adaptive and Dynamic Support Vector Machine Ensemble With Time Window in Corporate Financial Risk Prediction63 cited
  • 2013A REVIEW ON DATA MINING IN BANKING SECTOR51 cited
  • 2013Normalized Online Learning49 cited
  • 2015A customer classification prediction model based on machine learning techniques42 cited
  • 2020Predicting Loan Approval of Bank Direct Marketing Data Using Ensemble Machine Learning Algorithms26 cited
  • 2022A Machine Learning Framework towards Bank Telemarketing Prediction25 cited
  • 2018Prediction of customer behaviour analysis using classification algorithms25 cited
  • 2017On identifying potential direct marketing consumers using adaptive boosted support vector machine

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24 cited
  • 2016Evaluation of Classification and Ensemble Algorithms for Bank Customer Marketing Response Prediction21 cited
  • 2018Optimizing the prediction of telemarketing target calls by a classification technique20 cited
  • 2019Bank Marketing Data Mining using CRISP-DM Approach18 cited
  • 2016The motivations for big data mining technologies adoption in saudi banks18 cited