Recent advances in communication enable individuals to use phones and computers to
access information on the web. E-commerce has seen rapid development, eg, Alibaba has …

Click-Through Rate (CTR) prediction aims to predict the possibility of users clicking on
products, which has become the core task of advertising recommendation systems. Due to …

Click-through rate (CTR) prediction plays a central role in online advertising and
recommendation systems. In recent years, with the successful application of deep neural …

Click-through rate (CTR) prediction is a crucial topic in online advertising system. Early
researchers proposed numerous shallow models to analyze this issue, such as logistic …

The prediction of click-through rate is a challenging problem in the aspect of online
advertising. Recently, researchers have proposed deep learning-based models that follow a …

Recently, click-through rate (CTR) prediction is a challenge problem in the aspect of online
advertising. Some researchers have proposed deep learning-based models that follow a …

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 (CTR) prediction is a term used to predict the probability of a user clicking
on an ad or item and has become a popular research area in advertising. As the volume of …

Existing click-through rate prediction models employ both a shallow model and a deep
neural model for better feature interaction. The former shallow model aims to extract …

Online advertising is becoming an important direction in the advertising industry with its
strengths in diverse users, strong interactions, real-time feedback, and expandability. Online …