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User Behavior Modeling (UBM) plays a critical role in user interest learning, which has been extensively used in recommender systems.
Collaborative filtering for implicit feedback datasets
Yifan Hu, Yehuda Koren, and Chris Volinsky · 2008
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Neural turing machines
Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
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Learning hierarchical representation model for next basket recommendation
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Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, and Linas Baltrunas et al · 2016
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Parallel recurrent neural network architectures for feature-rich session-based recommendations
Balázs Hidasi, Massimo Quadrana, and Alexandros Karatzoglou et al · 2016
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Ask me anything: Dynamic memory networks for natural language processing
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Improved recurrent neural networks for session-based recommendations
Yong Kiam Tan, Xinxing Xu, and Yong Liu · 2016
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Neural attentive session-based recommendation
Jing Li and Pengjie Ren, et al · 2017
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Personalizing session-based recommendations with hierarchical recurrent neural networks
Massimo Quadrana, Alexandros Karatzoglou, and Balázs Hidasi et al · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, and Niki Parmar et al · 2017
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Sequential recommendation with user memory networks
Xu Chen, Hongteng Xu, and Yongfeng Zhang et al · 2018
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Recurrent neural networks with top-k gains for session-based recommendations
Balázs Hidasi and Alexandros Karatzoglou · 2018
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Improving sequential recommendation with knowledge-enhanced memory networks
Jin Huang, Wayne Xin Zhao, and Hongjian Dou et al · 2018
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Self-attentive sequential recommendation
Wang-Cheng Kang and Julian J. McAuley · 2018
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Modeling task relationships in multi-task learning with multi-gate mixture-of-experts
Jiaqi Ma, Zhe Zhao, and Xinyang Yi et al · 2018
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Personalized top-n sequential recommendation via convolutional sequence embedding
Jiaxi Tang and Ke Wang · 2018
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Neural memory streaming recommender networks with adversarial training
Qinyong Wang, Hongzhi Yin, and Zhiting Hu et al · 2018
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Deep interest network for click-through rate prediction
Guorui Zhou, Xiaoqiang Zhu, and Chengru Song et al · 2018
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Micro behaviors: A new perspective in e-commerce recommender systems
Meizi Zhou, Zhuoye Ding, and Jiliang Tang et al · 2018
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Behavior sequence transformer for e-commerce recommendation in alibaba
Qiwei Chen, Huan Zhao, and Wei Li et al · 2019
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Deep session interest network for click-through rate prediction
Yufei Feng, Fuyu Lv, and Weichen Shen et al · 2019
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Neural multi-task recommendation from multi-behavior data
Chen Gao, Xiangnan He, and Dahua Gan et al · 2019
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Buying or browsing?: Predicting real-time purchasing intent using attention-based deep network with multiple behavior
Long Guo, Lifeng Hua, and Rongfei Jia et al · 2019
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Tissa: A time slice self-attention approach for modeling sequential user behaviors
Chenyi Lei, Shouling Ji, and Zhao Li · 2019
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π \pi -net: A parallel information-sharing network for shared-account cross-domain sequential recommendations
Muyang Ma, Pengjie Ren, and Yujie Lin et al · 2019
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Practice on long sequential user behavior modeling for click-through rate prediction
Qi Pi, Weijie Bian, and Guorui Zhou et al · 2019
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Sequential recommendation with graph neural networks
Jianxin Chang, Chen Gao, and Yu Zheng et al · 2021
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Graph heterogeneous multi-relational recommendation
Chong Chen, Weizhi Ma, and Min Zhang et al · 2021
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End-to-end user behavior retrieval in click-through rate prediction model
Qiwei Chen, Changhua Pei, and Chao Li et al · 2021
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Self-supervised learning on users’ spontaneous behaviors for multi-scenario ranking in e-commerce
Yulong Gu, Wentian Bao, and Dan Ou et al · 2021
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DA-GCN: A domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation
Lei Guo, Li Tang, and Tong Chen et al · 2021
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Semi: a sequential multi-modal information transfer network for e-commerce micro-video recommendations
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Kan Ren, Jiarui Qin, and Yuchen Fang et al · 2019
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Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer
Fei Sun, Jun Liu, and Jian Wu et al · 2019
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Sequential recommender systems: Challenges, progress and prospects
Shoujin Wang, Liang Hu, and Yan Wang et al · 2019
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A simple convolutional generative network for next item recommendation
Fajie Yuan, Alexandros Karatzoglou, and Ioannis Arapakis et al · 2019
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Feature-level deeper self-attention network for sequential recommendation
Tingting Zhang, Pengpeng Zhao, and Yanchi Liu et al · 2019
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Deep interest evolution network for click-through rate prediction
Guorui Zhou, Na Mou, and Ying Fan et al · 2019
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Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations
Hui Fang, Danning Zhang, and Yiheng Shu et al · 2020
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Chenyi Lei, Yong Liu, and Lingzi Zhang et al · 2021
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Noninvasive self-attention for side information fusion in sequential recommendation
Chang Liu, Xiaoguang Li, and Guohao Cai et al · 2021
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Knowledge-enhanced hierarchical graph transformer network for multi-behavior recommendation
Lianghao Xia, Chao Huang, and Yong Xu et al · 2021
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Graph meta network for multi-behavior recommendation
Lianghao Xia, Yong Xu, and Chao Huang et al · 2021
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Deep learning for click-through rate estimation
Weinan Zhang, Jiarui Qin, and Wei Guo et al · 2021
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Sampling is all you need on modeling long-term user behaviors for CTR prediction
Yue Cao, Xiaojiang Zhou, and Jiaqi Feng et al · 2022
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MISS: multi-interest self-supervised learning framework for click-through rate prediction
Wei Guo, Can Zhang, and Zhicheng He et al · 2022
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Adversarial filtering modeling on long-term user behavior sequences for click-through rate prediction
Xiaochen Li, Jian Liang, and Xialong Liu et al · 2022
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Context and attribute-aware sequential recommendation via cross-attention
Ahmed Rashed, Shereen Elsayed, and Lars Schmidt-Thieme · 2022
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Sequential modeling with multiple attributes for watchlist recommendation in e-commerce
Uriel Singer, Haggai Roitman, and Yotam Eshel et al · 2022
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Contrastive meta learning with behavior multiplicity for recommendation
Wei Wei, Chao Huang, and Lianghao Xia et al · 2022
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Decoupled side information fusion for sequential recommendation
Yueqi Xie, Peilin Zhou, and Sunghun Kim · 2022
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Multi-behavior sequential transformer recommender
Enming Yuan, Wei Guo, and Zhicheng He et al · 2022
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Deepvt: Deep view-temporal interaction network for news recommendation
Xuanyu Zhang, Qing Yang, and Dongliang Xu et al · 2022
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Learning to retrieve user behaviors for click-through rate estimation
Jiarui Qin, Weinan Zhang, and Rong Su et al · 2023
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