An accurate estimation of the click-through rate (CTR), that is, the probability of clicking on a
recommended advertisement item online, is crucial for advertising agencies to make …

Click-through rate (CTR) prediction is a research hotspot in the field of recommendation
systems and online advertising. Because of the diversity, large-scale, and high real-time …

Click-through rate (CTR) prediction is crucial in computational advertising and
recommendation systems, with superior performance relying on effectively modeling feature …

Click-through rate (CTR) prediction is crucial for computing advertisement and
recommender systems. The key challenge of CTR prediction is to accurately capture user …

Click-through rate prediction has become a hot research direction in the field of advertising.
It is important to build an effective CTR prediction model. However, most existing models …

The click-through rate (CTR) forecast is among the mainstream research directions in the
domain of recommender systems, especially in online advertising suggestions. Among …

In this paper, we conceive a new kind of output layer design in deep neural networks for the
multi-class problems. The traditional output layer is set by the one-to-one method. For the …

Early diagnosis requires cardiovascular disease forecasting. Past patient interests can
improve machine learning predictions. This study uses a Generative Adversarial Network …

Click-through rate (CTR) is a crucial measure used in system of recommendations and
online advertising. It assesses how effective advertisements or content are by gauging the …

Ad click-through rate prediction is a key problem in the field of computational advertising. In
this paper, LR model, Random Forest model, GDBT model and LightGBM model are used to …