A Survey of Online Advertising Click-Through Rate Prediction Models

In recent years, online advertising sales have been the main economic sources of Internet companies such as Google, Facebook, Snap, Pinterest, and Baidu. Advertising click-through rate measures the ratio of users who click an advertisement to the total users who view the advertisement. The click-through rate is very important for Internet companies' online advertisements quality. The click-through rate of online advertising is related to many factors, including gender, age, type of advertisement, and the timely and effective prediction of the click-through rate of online advertising as well as advertisement text. In recent years, the click-through rate of online advertising has become one of the hot areas of research in industry and academia. Advertising prediction models are generally divided into two categories: shallow learning models and deep learning models [1]. This paper surveys Click-Through Rate (CTR) prediction models, discusses the problems in the current advertising click rate prediction models, and points out future research trends.