Analysis of the Click through Rate of Chinese Netizens through Social Software based on DeepFM Algorithm
Bo Li, Xiao Zhang, Kewei Li, Yan Jingyi · Journal of Physics Conference Series · 2019
Abstract Advertising as an important means of marketing, plays an important role in the promotion of commercial services, but its profit efficiency has not been optimistic. How to reduce the push cost and improve the accuracy rate of advertising is the algorithm problem of various enterprises. Chinese netizens have a large base and a large proportion use social software. It is a novel idea to analyze the click-through rate of Chinese netizens’advertisements through the data provided by social software. Based on the idea of lookalike crowd expansion, this paper uses DeepFM algorithm and designs the corresponding experimental process to analyze and predict the clicks of Chinese netizens through social software.