Disentangled Contrastive Learning for Social Recommendation-Reference-Cited by-同舟云学术

Disentangled Contrastive Learning for Social Recommendation

Published:2022-10-17 Issue: Volume: Page:
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Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Wu Jiahao¹,Fan Wenqi²,Chen Jingfan³,Liu Shengcai⁴,Li Qing²,Tang Ke⁴

Affiliation:

1. Southern University of Science and Technology & The Hong Kong Polytechnic University, Shenzhen, Guangdong, China

2. The Hong Kong Polytechnic University, Hong Kong, China

3. The Hong Kong Polytechnic University & Centre for Artificial Intelligence and Robotics (HKISI_CAS), Hong Kong, China

4. Southern University of Science and Technology, Shenzhen, Guangdong, China

Funder

Guangdong Provincial Key Laboratory

The Hong Kong Polytechnic University

Guangdong Introducing Innovative and Entrepreneurial Teams

Shenzhen Peacock Plan

Hong Kong Research Grants Council

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557583

Reference41 articles.

1. Knowledge-enhanced Black-box Attacks for Recommendations

2. Ting Chen , Simon Kornblith , Mohammad Norouzi , and Geoffrey E. Hinton . 2020. A simple framework for contrastive learning of visual representations . In Proceedings of the 37th International Conference on Machine Learning. Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020. A simple framework for contrastive learning of visual representations. In Proceedings of the 37th International Conference on Machine Learning.

3. Social Influence: Compliance and Conformity

4. Epidemic Graph Convolutional Network

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