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Sequential Recommendationdescribes a set of techniques to model dynamic user behavior in order to predict future interactions in sequential user data.
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BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer. In CIKM . 1441–1450
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Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning
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Zhuofeng Wu, Sinong Wang, Jiatao Gu, Madian Khabsa, Fei Sun, and Hao Ma. 2020d · 2020
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What should not be contrastive in contrastive learning
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Contrastive Pre-training for Sequential Recommendation
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Self-supervised Learning for Deep Models in Recommendations
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Time Matters: Sequential Recommendation with Complex Temporal Information. In SIGIR . 1459–1468
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Contrastive Learning for Debiased Candidate Generation at Scale
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Graph Contrastive Learning with Adaptive Augmentation
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SimCSE: Simple Contrastive Learning of Sentence Embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer
Zhiwei Liu, Ziwei Fan, Yu Wang, and Philip S. Yu. 2021 · 2021
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Denoising implicit feedback for recommendation. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining . 373–381
Wenjie Wang, Fuli Feng, Xiangnan He, Liqiang Nie, and Tat-Seng Chua. 2021 · 2021
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