Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings-Reference-Cited by-同舟云学术

Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2022
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Author:

Wang Kai¹,Liu Yu²,Sheng Quan Z.³

Affiliation:

1. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, China and Intelligent Computing Laboratory, School of Computing, Macquarie University, Australia

2. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, China

3. Intelligent Computing Laboratory, School of Computing, Macquarie University, Australia

Funder

National Natural Science Foundation in China

Australian Research Council (ARC) Discovery Project

Fundamental Research Fund for Central University

Australian Research Council (ARC) Future Fellowship

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3485447.3511927

Reference38 articles.

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3. Antoine Bordes , Alberto García-Durán , Jason Weston , and Oksana Yakhnenko . 2013 . Translating Embeddings for Modeling Multi-relational Data . In Proceedings of the 27th Annual Conference on Neural Information Processing Systems , December 5-8, 2013, Lake Tahoe, Nevada, United States. 2787–2795. Antoine Bordes, Alberto García-Durán, Jason Weston, and Oksana Yakhnenko. 2013. Translating Embeddings for Modeling Multi-relational Data. In Proceedings of the 27th Annual Conference on Neural Information Processing Systems, December 5-8, 2013, Lake Tahoe, Nevada, United States. 2787–2795.

4. A semantic matching energy function for learning with multi-relational data

5. Low-Dimensional Hyperbolic Knowledge Graph Embeddings

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