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Journal of Engineering and Applied Sciences
Year: 2019  |  Volume: 14  |  Issue: 9 SI  |  Page No.: 10560 - 10568

CTR Prediction with Deep Neural Networks

Mustafa Radif and Atheer Alrammahi    

Abstract: Ad effectiveness on online platforms including Facebook and Google is a challenge for businesses. Since, ad networks use algorithms, ad effectiveness as measured by CTRs is not well understood by marketing and sales executives. CTR prediction with deep neural networks can improve ad CTRs. The AI solution for ad CTRs is useful across industry sectors. In the solution, RNN Models learn representations of sequences by maintaining internal states which are updated sequentially and used as proxy for target prediction. Evidence from research shows that deep neural networks could help businesses enhance CTRs.

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