What does this research mean for the field?

Contrastive self-supervised learning provides a dominant and effective approach for mitigating data sparsity and cold-start issues in recommender systems, and its various methods can be unified under a taxonomy of view generation strategies, contrastive tasks, and contrastive objectives. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

October 9, 2023ACM Transactions on Information Systems

Contrastive Self-supervised Learning in Recommender Systems: A Survey

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MJMengyuan JingKey Laboratory of Guangdong Province YZYanmin ZhuShanghai Jiao Tong University TZTianzi ZangWuhan University

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Cite This Study

Jing et al. (2023) studied this question.

synapsesocial.com/papers/6a0f64b78090e499da5fbf0b https://doi.org/10.1145/3627158

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Contrastive Self-supervised Learning in Recommender Systems: A Survey

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Member takes

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Cite This Study

Contrastive Self-supervised Learning in Recommender Systems: A Survey

Discussion

Member takes

Implication

Key Points

Cite This Study

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