Click-through rate prediction in online advertising: A literature review

作者：

Highlights：

• We make a comprehensive literature review on state-of-the-art and latest CTR prediction research, with a special focus on modeling frameworks.

• We give a classification of state-of-the-art CTR prediction models in the extant literature, and present modeling frameworks, advantages and disadvantages, and implementations in CTR prediction.

• We summarize CTR prediction models with respect to the complexity and the order of feature interactions, and performance evaluation on various datasets.

• We identify challenges and interesting perspectives worthy of further exploration.

摘要

•We make a comprehensive literature review on state-of-the-art and latest CTR prediction research, with a special focus on modeling frameworks.•We give a classification of state-of-the-art CTR prediction models in the extant literature, and present modeling frameworks, advantages and disadvantages, and implementations in CTR prediction.•We summarize CTR prediction models with respect to the complexity and the order of feature interactions, and performance evaluation on various datasets.•We identify challenges and interesting perspectives worthy of further exploration.

论文关键词：Click-through rate,CTR prediction,Prediction models,Online advertising

论文评审过程：Received 20 July 2021, Revised 22 November 2021, Accepted 19 December 2021, Available online 5 January 2022, Version of Record 5 January 2022.

论文官网地址：https://doi.org/10.1016/j.ipm.2021.102853