Computer Science ›› 2019, Vol. 46 ›› Issue (7): 38-49.doi: 10.11896/j.issn.1002-137X.2019.07.006

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Review on Click-through Rate Prediction Models for Display Advertising

LIU Meng-juan1,ZENG Gui-chuan1,YUE Wei1,QIU Li-zhou1,WANG Jia-chang2   

  1. (School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China)1
    (Nuclear Power Institute of China,Chengdu 610213,China)2
  • Received:2018-07-05 Online:2019-07-15 Published:2019-07-15

Abstract: In recent years,the study of the click-through rate prediction model has attracted much attention from academia and industry.As for the existing CTR prediction models for displaying targeted advertising,this paper studied the preprocessing techniques for features of samples,the CTR prediction schemes based on traditional machine learning models and the latest deep learning models,and the main performance evaluation indexes of CTR prediction models.Specially,these typical CTR prediction schemes were evaluated based on a public dataset,further some quantitative analysis and performance comparison were given.Finally,the problems and research trends in CTR prediction were discussed.

Key words: Click-through rate prediction, Targeted advertising, Logistic regression, Factorization machine, Deep learning

CLC Number: 

  • TP311
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