… 摘要(英) Click-through rate prediction has been an essential application in many content-…
Deep crossing: web-scale modeling without manually crafted combinatorial features. In …

… This paper aims to predict a users’ next clicking item based … performance on deep
learning-based ranking models, we … Gai, “Deep interest network for click-through rate prediction,” …

… , we can measure subtle changes in click-through rate,watch time, and … We use a deep neural
network with similar architecture … metricscompared to predicting click-through rate directly. …

… role in the accuracy of click-through-rate (CTR) estimation in … tion-machine based neural
network for CTR prediction [C] / / … tion machines for click-through rate prediction in display …

… deep learning models of the click-through rate can enhance the prediction of the winning
price or not. … structure is an embedding layer and several layers of dense neuron network. 14 …

… Feature generation by convolutional neural network for click-through rate prediction [C]//The …
interaction for click-through rate prediction [C]//Proceedings of the 13th ACM Conference on …

… Click-through rate (CTR) prediction holds a significant role within … by combining traditional
generalized linear models with deep neural networks. DIN[7] … and a target item to be predicted, …

… 在ctr 预估中,Deep Interest Network for Click-Through Rate Prediction 出发点类似.在推荐
场景中,文章Feature Aware Multi-Head Attention 在手淘猜你喜欢排序模型中的应用 .这些都是…

… neural networks has also emerged. Welling et al.[27] proposed Graph Convolutional Network
(GCN) to update the features of … driven exploration for deep click-through rate prediction. In …