Journal of Cybersecurity and Information Management

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https://doi.org/10.54216/JCIM

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2690-6775ISSN (Online) 2769-7851ISSN (Print)

Volume 9 , Issue 1 , PP: 27-39, 2022 | Cite this article as | XML | Html | PDF | Full Length Article

A Proposed Predictive Model for Business Telemarketing Information Management

Mohamed Elsharkawy 1 * , I.S. Farahat 2

  • 1 Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura, Egypt - (mohmed.elsharkawy@mans.edu.eg)
  • 2 Faculty of computers and information, Luxor University, Egypt - (ishawky@fci.luxor.edu)
  • Doi: https://doi.org/10.54216/JCIM.090103

    Received: June 05, 2021 Accepted: November 30, 2021
    Abstract

    Bank telemarketing is a prominent way of direct marketing approach in which the telemarketers ask possible clients by mobile phones for purchasing or subscribing to bank product or service. But the clients who are not interested in the offers or promotions by the bank telemarketing commonly face negative interaction owing to the thought of thinking the telemarketing as spam. Therefore, the recent developments of deep learning (DL) models can be used to realize the predictive models for bank telemarketing applications. This study develops an effective Archimedes Optimization with Deep Belief Network based Predictive (AOA-DBNP) for bank telemarketing applications. The proposed AOA-DBNP technique primarily undergoes pre-processing for transforming the data as to useful format. In addition, the AOA-DBNP technique involves the use of the DBN model for the prediction process and finally, the AOA is applied for tuning the hyperparameters of DBN technique. The utilization of AOA helps to optimally select the hyperparameters of the DBN model in such a way that the predictive performance gets improved to a maximum extent. To showcase the enhanced efficiency of the AOA-DBNP manner, a comprehensive comparative results analysis reported the better performance of the AOA-DBNP model. 

    Keywords :

    Bank telemarketing, Deep learning, Business section, Parameter tuning, Data mining

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    Cite This Article As :
    Elsharkawy, Mohamed. , Farahat, I.S.. A Proposed Predictive Model for Business Telemarketing Information Management. Journal of Cybersecurity and Information Management, vol. , no. , 2022, pp. 27-39. DOI: https://doi.org/10.54216/JCIM.090103
    Elsharkawy, M. Farahat, I. (2022). A Proposed Predictive Model for Business Telemarketing Information Management. Journal of Cybersecurity and Information Management, (), 27-39. DOI: https://doi.org/10.54216/JCIM.090103
    Elsharkawy, Mohamed. Farahat, I.S.. A Proposed Predictive Model for Business Telemarketing Information Management. Journal of Cybersecurity and Information Management , no. (2022): 27-39. DOI: https://doi.org/10.54216/JCIM.090103
    Elsharkawy, M. , Farahat, I. (2022) . A Proposed Predictive Model for Business Telemarketing Information Management. Journal of Cybersecurity and Information Management , () , 27-39 . DOI: https://doi.org/10.54216/JCIM.090103
    Elsharkawy M. , Farahat I. [2022]. A Proposed Predictive Model for Business Telemarketing Information Management. Journal of Cybersecurity and Information Management. (): 27-39. DOI: https://doi.org/10.54216/JCIM.090103
    Elsharkawy, M. Farahat, I. "A Proposed Predictive Model for Business Telemarketing Information Management," Journal of Cybersecurity and Information Management, vol. , no. , pp. 27-39, 2022. DOI: https://doi.org/10.54216/JCIM.090103