Survey on Click-Through Rate Prediction Based on Deep Learning

Abstract

With regards to computer science, deep learning forms an essential research area. Recently, deep learning has made achievements on image processing, language understanding, data analysis, speech recognition, online advertising and so on. At the same time, display advertising has also become the most popular means of publicity with the rapid development in terms of the Internet, as well as the rapid expansion of the market of online advertising. Accurate advertising recommendation is the guarantee of Internet platform profits. The premise of accurate recommendation is accurate advertising click through rate prediction. Since 2015, the deep learning success has made the estimation of CTR results more accurate. Many CTR models have been used widely on a large amount of online platforms. This paper reviews several deep learning-based click-through rate prediction models for online advertising recently; classifies these prediction algorithms in the aspect of basic structure, complexity and main functions; and analyses the differences, advantages and the application. Finally, the survey is summarized and the future prospects of this field are envisaged.