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cs.IR2022★ 27 cited
Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search
Zhifang Fan, Dan Ou, Yulong Gu +7
Modeling user's historical feedback is essential for Click-Through Rate Prediction in personalized search and recommendation. Existing methods usually only model users' positive fe…
cs.IR2020
Adversarial Multimodal Representation Learning for Click-Through Rate Prediction
Xiang Li, Chao Wang, Jiwei Tan +3
For better user experience and business effectiveness, Click-Through Rate (CTR) prediction has been one of the most important tasks in E-commerce. Although extensive CTR prediction…