A Click-Through Rate Prediction Method Based on Cross-Importance of Multi-Order Features

14 May 2024

Papers citing "A Click-Through Rate Prediction Method Based on Cross-Importance of Multi-Order Features"

8 / 8 papers shown

Title
KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems Chongming Gao Shijun Li Wenqiang Lei Jiawei Chen Biao Li Peng Jiang Xiangnan He Jiaxin Mao Tat-Seng Chua 81 142 0 22 Feb 2022
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks Weiping Song Chence Shi Zhiping Xiao Zhijian Duan Yewen Xu Ming Zhang Jian Tang CML 87 857 0 29 Oct 2018
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems Jianxun Lian Xiaohuan Zhou Fuzheng Zhang Zhongxia Chen Xing Xie Guangzhong Sun BDL 56 1,048 0 14 Mar 2018
Squeeze-and-Excitation Networks Jie Hu Li Shen Samuel Albanie Gang Sun Enhua Wu 427 26,557 0 05 Sep 2017
Deep & Cross Network for Ad Click Predictions Ruoxi Wang Bin Fu Gang Fu Mingliang Wang 104 1,234 0 17 Aug 2017
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks Jun Xiao Hao Ye Xiangnan He Hanwang Zhang Leilei Gan Tat-Seng Chua 91 919 0 15 Aug 2017
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li Xiuqiang He 122 2,654 0 13 Mar 2017
Wide & Deep Learning for Recommender Systems Heng-Tze Cheng L. Koc Jeremiah Harmsen T. Shaked Tushar Chandra ... Zakaria Haque Lichan Hong Vihan Jain Xiaobing Liu Hemal Shah HAI VLM 190 3,662 0 24 Jun 2016