Self-supervised learning for recommender systems: A survey
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
[引用][C] Self-supervised learning for recommender systems: a survey
J Yu, H Yin, X Xia, T Chen, J Li… - IEEE Transactions on …, 2024 - espace.library.uq.edu.au
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
Self-Supervised Learning for Recommender Systems: A Survey
J Yu, H Yin, X Xia, T Chen, J Li… - IEEE Transactions on …, 2024 - computer.org
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
[PDF][PDF] Self-Supervised Learning for Recommender Systems: A Survey
J Yu, H Yin, X Xia, T Chen, J Li, Z Huang - researchgate.net
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
Self-Supervised Learning for Recommender Systems: A Survey
J Yu, H Yin, X Xia, T Chen, J Li, Z Huang - arXiv preprint arXiv:2203.15876, 2022 - arxiv.org
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
Self-Supervised Learning for Recommender Systems: A Survey
J Yu, H Yin, X Xia, T Chen, J Li, Z Huang - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
Self-Supervised Learning for Recommender Systems: A Survey
J Yu, H Yin, X Xia, T Chen, J Li, Z Huang - IEEE Transactions on …, 2024 - dl.acm.org
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …