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The significance of modeling long-term user interests for CTR prediction tasks in large-scale recommendation systems is progressively gaining attention among researchers and practitioners.
Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
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Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Anchorage, AK, USA) (KDD ’19) . Association for Computing Machinery, New York, NY, USA, 2671–2679
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AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (Beijing, China) (CIKM ’19) . Association for Computing Machinery, New York, NY, USA, 1161–1170
Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, and Jian Tang. 2019 · 2019
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Deep Interest Evolution Network for Click-Through Rate Prediction
Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, and Kun Gai. 2019 · 2019
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Search-Based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management (Virtual Event, Ireland) (CIKM ’20) . Association for Computing Machinery, New York, NY, USA, 2685–2692
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Yue Cao, Xiaojiang Zhou, Jiaqi Feng, Peihao Huang, Yao Xiao, Dayao Chen, and Sheng Chen. 2022 · 2022
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Clustering Based Behavior Sampling with Long Sequential Data for CTR Prediction. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (<conf-loc>, <city>Madrid</city>, <country>Spain</country>, </conf-loc>) (SIGIR ’22) . Association for Computing Machinery, New York, NY, USA, 2195–2200
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TWIN: TWo-Stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’23) . Association for Computing Machinery, New York, NY, USA, 3785–3794
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Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction
Qi Liu, Xuyang Hou, Haoran Jin, jin Chen, Zhe Wang, Defu Lian, Tan Qu, Jia Cheng, and Jun Lei. 2023 · 2023
Later among the works it cites.
Learning to Retrieve User Behaviors for Click-through Rate Estimation
Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Guangpeng Zhao, Hao Li, Ruiming Tang, Xiuqiang He, and Yong Yu. 2023 · 2023
Later among the works it cites.