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Title: GitHub - Coder-Yu/SELFRec: An open-source framework for self-supervised recommender systems.

Open Graph Title: GitHub - Coder-Yu/SELFRec: An open-source framework for self-supervised recommender systems.

X Title: GitHub - Coder-Yu/SELFRec: An open-source framework for self-supervised recommender systems.

Description: An open-source framework for self-supervised recommender systems. - Coder-Yu/SELFRec

Open Graph Description: An open-source framework for self-supervised recommender systems. - Coder-Yu/SELFRec

X Description: An open-source framework for self-supervised recommender systems. - Coder-Yu/SELFRec

Mail addresses
h.yin1@uq.edu.au

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@Coder-Yu https://github.com/Coder-Yu
@xiaxin1998https://github.com/xiaxin1998
survey paperhttps://arxiv.org/abs/2203.15876
tutorial pagehttps://ssl-recsys.github.io/
https://github.com/Coder-Yu/SELFRec#architecture
https://raw.githubusercontent.com/Coder-Yu/SELFRec/main/selfrec.jpg
https://github.com/Coder-Yu/SELFRec
https://github.com/Coder-Yu/SELFRec#features
https://github.com/Coder-Yu/SELFRec#how-to-use
https://github.com/Coder-Yu/SELFRec#implemented-models
Self-Attentive Sequential Recommendationhttps://cseweb.ucsd.edu/~jmcauley/pdfs/icdm18.pdf
Contrastive Learning for Sequential Recommendationhttps://arxiv.org/abs/2010.14395
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformerhttps://dl.acm.org/doi/pdf/10.1145/3357384.3357895
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendationhttps://arxiv.org/abs/2209.02544
Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendationhttps://arxiv.org/abs/2112.08679
Towards Representation Alignment and Uniformity in Collaborative Filteringhttps://arxiv.org/abs/2206.12811
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learninghttps://arxiv.org/abs/2202.06200
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systemshttps://keg.cs.tsinghua.edu.cn/jietang/publications/KDD21-Huang-et-al-MixGCF.pdf
Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendationhttps://dl.acm.org/doi/abs/10.1145/3442381.3449844
Self-supervised Graph Learning for Recommendationhttps://dl.acm.org/doi/10.1145/3404835.3462862
Socially-Aware Self-supervised Tri-Training for Recommendationhttps://arxiv.org/abs/2106.03569
Bootstrapping User and Item Representations for One-Class Collaborative Filteringhttps://arxiv.org/abs/2105.06323
Self-supervised Learning for Large-scale Item Recommendationshttps://dl.acm.org/doi/abs/10.1145/3459637.3481952
SelfCF: A Simple Framework for Self-supervised Collaborative Filteringhttps://arxiv.org/abs/2107.03019
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendationhttps://dl.acm.org/doi/10.1145/3397271.3401063
Matrix Factorization Techniques for Recommender Systemshttps://ieeexplore.ieee.org/abstract/document/5197422
https://github.com/Coder-Yu/SELFRec#leaderboard
https://github.com/Coder-Yu/SELFRec#implement-your-model
https://github.com/Coder-Yu/SELFRec#related-datasets
Doubanhttps://pan.baidu.com/s/1hrJP6rq
LastFMhttp://files.grouplens.org/datasets/hetrec2011/hetrec2011-lastfm-2k.zip
Yelphttps://www.dropbox.com/sh/h97ymblxt80txq5/AABfSLXcTu0Beib4r8P5I5sNa?dl=0
Amazon-Bookhttps://www.dropbox.com/sh/20l0xdjuw0b3lo8/AABBZbRg9hHiN42EHqBSvLpta?dl=0
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