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Iterative Boosting Deep Neural Networks for Predicting Click-Through Rate
[article]
2020
arXiv
pre-print
The click-through rate (CTR) reflects the ratio of clicks on a specific item to its total number of views. It has significant impact on websites' advertising revenue. Learning sophisticated models to understand and predict user behavior is essential for maximizing the CTR in recommendation systems. Recent works have suggested new methods that replace the expensive and time-consuming feature engineering process with a variety of deep learning (DL) classifiers capable of capturing complicated
arXiv:2007.13087v1
fatcat:aujqcpa4ofgsjduankwjwow5mu