Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System-Reference-Cited by-同舟云学术

Multi-level Cross-view Contrastive Learning for Knowledge-aware Recommender System

Published:2022-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zou Ding¹,Wei Wei¹,Mao Xian-Ling²,Wang Ziyang¹,Qiu Minghui³,Zhu Feida⁴,Cao Xin⁵

Affiliation:

1. Huazhong University of Science and Technology, Wuhan, China

2. Beijing Institute of Technology, Beijing, China

3. Alibaba Group, Hangzhou, China

4. Singapore Management University, Singapore, Singapore

5. The University of New South Wales, Sydney, NSW, Australia

Funder

National Natural Science Foundation of China

CCF-AFSG Research Fund

National Research Foundation (NRF) of Singapore

Fund of Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3532025

Reference59 articles.

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3. Yixin Cao Xiang Wang Xiangnan He Zikun Hu and Tat-Seng Chua. 2019. Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences. In WWW. 151--161. Yixin Cao Xiang Wang Xiangnan He Zikun Hu and Tat-Seng Chua. 2019. Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences. In WWW. 151--161.

4. Jie Chen , Haw-ren Fang, and Yousef Saad . 2009. Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection. Journal of Machine Learning Research ( 2009 ). Jie Chen, Haw-ren Fang, and Yousef Saad. 2009. Fast Approximate kNN Graph Construction for High Dimensional Data via Recursive Lanczos Bisection. Journal of Machine Learning Research (2009).

5. Ting Chen Simon Kornblith Mohammad Norouzi and Geoffrey Hinton. 2020 a. A simple framework for contrastive learning of visual representations. In ICML. 1597--1607. Ting Chen Simon Kornblith Mohammad Norouzi and Geoffrey Hinton. 2020 a. A simple framework for contrastive learning of visual representations. In ICML. 1597--1607.

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