An Ensemble Architecture Based on Deep Learning Model for Click Fraud Detection in Pay-Per-Click Advertisement Campaign

Batool, Amreen; Byun, Yung-Cheol

doi:10.1109/ACCESS.2022.3211528

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An Ensemble Architecture Based on Deep Learning Model for Click Fraud Detection in Pay-Per-Click Advertisement Campaign

Author(s): Amreen Batool ¹ , Yung-Cheol Byun ²

Publication date (Print): 2022

Journal: IEEE Access

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

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Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs

Yvan Lucas, Pierre-Edouard Portier, Léa Laporte … (2020)

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Enhanced credit card fraud detection based on SVM-recursive feature elimination and hyper-parameters optimization

Naoufal Rtayli, Nourddine Enneya (2020)

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Improvement of learning for CNN with ReLU activation by sparse regularization

Hidenori Ide, Takio Kurita (2017)

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Amreen Batool: (View ORCID Profile)

Yung-Cheol Byun: (View ORCID Profile)

Journal

Title: IEEE Access

Abbreviated Title: IEEE Access

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN (Electronic): 2169-3536

Publication date Created: 2022

Publication date (Print): 2022

Volume: 10

Pages: 113410-113426

Affiliations

[1 ]Department of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju, South Korea

[2 ]Department of Computer Engineering, Major of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju, South Korea

Article

DOI: 10.1109/ACCESS.2022.3211528

SO-VID: 221d171e-e02b-4e5b-9a9f-5a89425dfd2c

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https://creativecommons.org/licenses/by/4.0/legalcode

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An Ensemble Architecture Based on Deep Learning Model for Click Fraud Detection in Pay-Per-Click Advertisement Campaign

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Higher order chromatin architecture

Most cited references 64

Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs

Enhanced credit card fraud detection based on SVM-recursive feature elimination and hyper-parameters optimization

Improvement of learning for CNN with ReLU activation by sparse regularization

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