Category-Specific CNN for Visual-aware CTR Prediction at JD.com

1.运用场景

    CTR模型/加入图像特征。

2.创新点

    propose CSCNN,a novel visual embedding module specially for CTR prediction.The key idea is to conduct category-specific channel and spatial self-attention to emphasize features that are both important and category related.
    build efficient infrastructure to apply CNN in the real online e-commerce advertising system.

3.算法原理

3.1 网络框架

Category-Specific CNN for Visual-aware CTR Prediction at JD.com_第1张图片

3.2 CSCNN

Category-Specific CNN for Visual-aware CTR Prediction at JD.com_第2张图片
Category-Specific CNN for Visual-aware CTR Prediction at JD.com_第3张图片

    CSCNN论文

4.算法理解

    引入visual embedding,且训练图像的特征时与物品类别对应,使特征能更好的用于CTR模型。

你可能感兴趣的:(Category-Specific CNN for Visual-aware CTR Prediction at JD.com)