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Shared-account Cross-domain Sequential recommendation (SCSR) is the task of recommending the next item based on a sequence of recorded user behaviors, where multiple users share a single account, and their behaviours are available in multiple domains.
Amazon.com recommendations: Item-to-item collaborative filtering
Greg Linden, Brent Smith, and Jeremy York · 2003
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Transfer learning in collaborative filtering for sparsity reduction
Weike Pan, Evan Wei Xiang, Nathan Nan Liu, and Qiang Yang · 2010
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Cross-domain collaboration recommendation
Jie Tang, Sen Wu, Jimeng Sun, and Hang Su · 2012
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Cross-system user modeling and personalization on the social web
Fabian Abel, Eelco Herder, Geert-Jan Houben, Nicola Henze, and Daniel Krause · 2013
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User identification within a shared account: Improving ip-tv recommender performance
Zhijin Wang, Yan Yang, Liang He, and Junzhong Gu · 2014
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Experience individualization on online tv platforms through persona-based account decomposition
Payal Bajaj and Sumit Shekhar · 2016
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Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk · 2016
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Passenger prediction in shared accounts for flight service recommendation
Yafeng Zhao, Jian Cao, and Yudong Tan · 2016
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Neural collaborative filtering
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua · 2017
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Personalizing session-based recommendations with hierarchical recurrent neural networks
Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, and Paolo Cremonesi · 2017
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Conet: Collaborative cross networks for cross-domain recommendation
Guangneng Hu, Yu Zhang, and Qiang Yang · 2018
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Identifying users behind shared accounts in online streaming services
Jyun-Yu Jiang, Cheng-Te Li, Yian Chen, and Wei Wang · 2018
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Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, and Pong Eksombatchai · 2018
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Cross-domain novelty seeking trait mining for sequential recommendation
Fuzhen Zhuang, Yingmin Zhou, Fuzheng Zhang, Xiang Ao, Xing Xie, and Qing He · 2018
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Origin-destination matrix prediction via graph convolution: A new perspective of passenger demand modeling
Yuandong Wang, Hongzhi Yin, Hongxu Chen, Tianyu Wo, Jie Xu, and Kai Zheng · 2019
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Social influence-based group representation learning for group recommendation
Hongzhi Yin, Qinyong Wang, Kai Zheng, Zhixu Li, Jiali Yang, and Xiaofang Zhou · 2019
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Cross-domain recommendation via preference propagation graphnet
Cheng Zhao, Chenliang Li, and Cong Fu · 2019
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Group recommendation with latent voting mechanism
Lei Guo, Hongzhi Yin, Qinyong Wang, Bin Cui, Zi Huang, and Lizhen Cui · 2020
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Cross domain recommendation via bi-directional transfer graph collaborative filtering networks
Meng Liu, Jianjun Li, Guohui Li, and Peng Pan · 2020
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Online multi-modal hashing with dynamic query-adaption
Xu Lu, Lei Zhu, Zhiyong Cheng, Liqiang Nie, and Huaxiang Zhang · 2019
Cited alongside, same era.
π \pi -net: A parallel information-sharing network for shared-account cross-domain sequential recommendations
Muyang Ma, Pengjie Ren, Yujie Lin, Zhumin Chen, Jun Ma, and Maarten de Rijke · 2019
Cited alongside, same era.
Parallel split-join networks for shared-account cross-domain sequential recommendation
Pengjie Ren, Yujie Lin, Muyang Ma, Zhumin Chen, Zhaochun Ren, Jun Ma, and Maarten de Rijke · 2019
Cited alongside, same era.
Kgat: Knowledge graph attention network for recommendation
Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, and Tat-Seng Chua · 2019
Cited alongside, same era.
Neural graph collaborative filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua · 2019
Cited alongside, same era.
Ruihong Qiu, Zi Huang, Jingjing Li, and Hongzhi Yin · 2020
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Intention nets: psychology-inspired user choice behavior modeling for next-basket prediction
Shoujin Wang, Liang Hu, Yan Wang, Quan Z Sheng, Mehmet Orgun, and Longbing Cao · 2020
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Overcoming data sparsity in group recommendation
H. Yin, Q. Wang, K. Zheng, Z. Li, and X. Zhou · 2020
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Hierarchical hyperedge embedding-based representation learning for group recommendation
Lei Guo, Hongzhi Yin, Tong Chen, Xiangliang Zhang, and Kai Zheng · 2021
Closest in time.
Graph learning based recommender systems: A review
Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z Sheng, Mehmet Orgun, Longbing Cao, Francesco Ricci, and Philip S Yu · 2021
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