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Session-based Recommendation (SR) aims to predict users' next click based on their behavior within a short period, which is crucial for online platforms.
Factorizing personalized markov chains for next-basket recommendation. In WWW . 811–820
Steffen Rendle, Christoph Freudenthaler, and Lars Schmidt-Thieme. 2010 · 2010
Earlier work this paper cites.
Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2015 · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Improved recurrent neural networks for session-based recommendations. In Proceedings of the 1st workshop on deep learning for recommender systems . 17–22
Yong Kiam Tan, Xinxing Xu, and Yong Liu. 2016 · 2016
Earlier work this paper cites.
When recurrent neural networks meet the neighborhood for session-based recommendation. In RecSys . 306–310
Dietmar Jannach and Malte Ludewig. 2017 · 2017
Earlier work this paper cites.
Neural attentive session-based recommendation. In CIKM . 1419–1428
Jing Li, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Tao Lian, and Jun Ma. 2017 · 2017
Earlier work this paper cites.
Focal loss for dense object detection. In Proceedings of the IEEE international conference on computer vision . 2980–2988
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár. 2017 · 2017
Earlier work this paper cites.
Recurrent neural networks with top-k gains for session-based recommendations. In CIKM . 843–852
Balázs Hidasi and Alexandros Karatzoglou. 2018 · 2018
Cited alongside, same era.
Self-attentive sequential recommendation. In 2018 IEEE International Conference on Data Mining (ICDM) . IEEE, 197–206
Wang-Cheng Kang and Julian McAuley. 2018 · 2018
Cited alongside, same era.
STAMP: short-term attention/memory priority model for session-based recommendation. In SIGKDD . 1831–1839
Qiao Liu, Yifu Zeng, Refuoe Mokhosi, and Haibin Zhang. 2018 · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
Cited alongside, same era.
Rethinking the item order in session-based recommendation with graph neural networks. In CIKM . 579–588
Ruihong Qiu, Jingjing Li, Zi Huang, and Hongzhi Yin. 2019 · 2019
Cited alongside, same era.
A simple convolutional generative network for next item recommendation. In WSDM . 582–590
Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M Jose, and Xiangnan He. 2019 · 2019
Later among the works it cites.
Exploiting cross-session information for session-based recommendation with graph neural networks
Ruihong Qiu, Zi Huang, Jingjing Li, and Hongzhi Yin. 2020 · 2020
Later among the works it cites.
Global context enhanced graph neural networks for session-based recommendation. In SIGIR . 169–178
Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, and Minghui Qiu. 2020 · 2020
Later among the works it cites.
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. In AAAI . 4503–4511
Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. 2021 · 2021
Later among the works it cites.
Social-aware Sparse Attention Network for Session-based Social Recommendation. In Findings of the Association for Computational Linguistics: EMNLP 2022 . Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 2173–2183
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Session-based recommendation with graph neural networks. In AAAI , Vol. 33. 346–353
Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, and Tieniu Tan. 2019 · 2019
Cited alongside, same era.
Graph Contextualized Self-Attention Network for Session-based Recommendation.. In IJCAI . 3940–3946
Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Victor S Sheng, Jiajie Xu, Fuzhen Zhuang, Junhua Fang, and Xiaofang Zhou. 2019 · 2019
Cited alongside, same era.
Kai Ouyang, Xianghong Xu, Chen Tang, Wang Chen, and Haitao Zheng. 2022 · 2022
Later among the works it cites.
Modeling Latent Autocorrelation for Session-Based Recommendation. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (Atlanta, GA, USA) (CIKM ’22) . Association for Computing Machinery, New York, NY, USA, 4605–4609
Xianghong Xu, Kai Ouyang, Liuyin Wang, Jiaxin Zou, Yanxiong Lu, Hai-Tao Zheng, and Hong-Gee Kim. 2022 · 2022
Later among the works it cites.