From electronic health records to terminology base: A novel knowledge base enrichment approach-Reference-Cited by-同舟云学术

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From electronic health records to terminology base: A novel knowledge base enrichment approach

Published:2021-01 Issue: Volume:113 Page:103628
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Zhang Jiaying,Zhang Zhixing,Zhang Huanhuan,Ma Zhiyuan,Ye Qi,He Ping,Zhou Yangming

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference41 articles.

1. Knowmore–knowledge base augmentation with structured web markup;Yu;Semant. Web,2019

2. B.D. Trsedya, J. Qi, R. Zhang, Entity alignment between knowledge graphs using attribute embeddings, in: Proceedings of Association for the Advance of Artificial Intelligence (AAAI), 2019, pp. 297–304.

3. M. Chen, Y. Tian, M. Yang, C. Zaniolo, Multilingual knowledge graph embeddings for cross-lingual knowledge alignment, in: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2017, pp. 1511–1517.

4. Y. Hao, Y. Zhang, S. He, K. Liu, J. Zhao, A joint embedding method for entity alignment of knowledge bases, in: Proceedings of China Conference on Knowledge Graph and Semantic Computing, 2016, pp. 3–14.

5. Z. Sun, W. Hu, C. Li, Cross-lingual entity alignment via joint attribute-preserving embedding, in: Proceedings of International Semantic Web Conference (ISWC), 2017, pp. 628–644.

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