SelfCF: A Simple Framework for Self-supervised Collaborative Filtering. (arXiv:2107.03019v2 [cs.IR] UPDATED)

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. Training with negative sampling on large datasets is computationally
expensive. Further, negative items should be carefully sampled under the
defined distribution, in order to avoid selecting an observed positive item in
the training dataset. Unavoidably, some negative items sampled from the
training dataset could be positive in the test set. In …

arxiv collaborative collaborative filtering filtering framework