MVGCL: Multi-View Graph Contrastive Learning for Service Recommendation-Reference-Cited by-同舟云学术

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MVGCL: Multi-View Graph Contrastive Learning for Service Recommendation

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Web Services (ICWS)
language:
Short-container-title:

Author:

Zou Guobing¹,Lin Shiyi¹,Hu Shengxiang¹,Gan Yanglan²,Zhang Bofeng³,Chen Yixin⁴

Affiliation:

1. Shanghai University,School of Computer Engineering and Science,Shanghai,China

2. Donghua University,School of Computer Science and Technology,Shanghai,China

3. Shanghai Polytechnic University,School of Computer and Information Engineering,Shanghai,China

4. Washington University in St. Louis,Department of Computer Science and Engineering,MO,USA

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10248204/10248227/10248229.pdf?arnumber=10248229

Reference37 articles.

1. LightGCN

2. A simple framework for contrastive learning of visual representations;chen;International Conference on Machine Learning (ICML),2020

3. Neural Graph Collaborative Filtering

4. A Knowledge Graph based Approach for Apps Permission Recommendation

5. Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning

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