Knowledge Graph Contrastive Learning for Recommendation
Author:
Affiliation:
1. University of Hong Kong, Hong Kong, Hong Kong
2. University of Hong Kong, Hong Kong, China
3. Wuhan University, Wuhan, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3477495.3532009
Reference55 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. Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In SIGIR. 335--344. Jingyuan Chen Hanwang Zhang Xiangnan He Liqiang Nie Wei Liu and Tat-Seng Chua. 2017. Attentive collaborative filtering: Multimedia recommendation with item-and component-level attention. In SIGIR. 335--344.
5. Ting Chen , Simon Kornblith , et almbox . 2020 . A simple framework for contrastive learning of visual representations. In ICML. PMLR , 1597--1607. Ting Chen, Simon Kornblith, et almbox. 2020. A simple framework for contrastive learning of visual representations. In ICML. PMLR, 1597--1607.
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