• Corpus ID: 235755396

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

@article{Zhou2021SelfCFAS,
  title={SelfCF: A Simple Framework for Self-supervised Collaborative Filtering},
  author={Xin Zhou and Aixin Sun and Yong Liu and Jie Zhang and Chunyan Miao},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.03019}
}
  • Xin ZhouAixin Sun C. Miao
  • Published 7 July 2021
  • Computer Science
  • ArXiv
Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions. Existing CF-based methods commonly adopt negative sampling to discriminate different items. That is, observed user-item pairs are treated as positive instances; unobserved pairs are considered as negative instances and are sampled under a defined distribution for training. Training with negative sampling on large datasets is computationally expensive. Further… 

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