Informed Multi-context Entity Alignment-Reference-Cited by-同舟云学术

Informed Multi-context Entity Alignment

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
language:
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Author:

Xin Kexuan¹,Sun Zequn²,Hua Wen¹,Hu Wei²,Zhou Xiaofang³

Affiliation:

1. The University of Queensland, Brisbane, QLD, Australia

2. Nanjing University, Nanjing, China

3. Hong Kong University of Science and Technology, Hong Kong, Hong Kong

Funder

Australian Research Council

Program A for Outstanding PhD Candidates of Nanjing University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3488560.3498523

Reference35 articles.

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2. Multi-Channel Graph Neural Network for Entity Alignment

3. Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment

4. Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

5. Xavier Glorot and Yoshua Bengio . 2010 . Understanding the difficulty of training deep feedforward neural networks . In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. 249--256 . Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. 249--256.

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