A click-through rate model of e-commerce based on user interest and temporal behavior

作者：

Highlights：

• TW-GRU is proposed to model the user’s historical behavior in a temporal order.

• An attention mechanism-based GRU network (A-GRU) is proposed.

• An ad click-through rate prediction model that incorporates user interest and implicit generalization features is proposed.

摘要

•TW-GRU is proposed to model the user’s historical behavior in a temporal order.•An attention mechanism-based GRU network (A-GRU) is proposed.•An ad click-through rate prediction model that incorporates user interest and implicit generalization features is proposed.

论文关键词：Click-through rate,Interest modeling,Gated recurrent unit

论文评审过程：Received 20 April 2022, Revised 9 June 2022, Accepted 15 June 2022, Available online 26 June 2022, Version of Record 28 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117896