Standard-Oriented Standard Knowledge Graph Construction and Applications System
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-85899-5_36
Reference10 articles.
1. Lecture Notes in Computer Science;J Cao,2020
2. Jiang, D., Ren, H., Cai, Y., Xu, J., Liu, Y., Leung, H.F.: Candidate region aware nested named entity recognition. Neural Netw. (2021)
3. Ren, H., Cai, Y., Chen, X., Wang, G., Li, Q.: A two-phase prototypical network model for incremental few-shot relation classification. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 1618–1629 (2020)
4. Tang, Z., Wan, B., Yang, L.: Word-character graph convolution network for Chinese named entity recognition. IEEE/ACM Trans. Audio Speech Lang. Process. 28, 1520–1532 (2020)
5. Tao, X., et al.: Mining health knowledge graph for health risk prediction. World Wide Web 23(4), 2341–2362 (2020)
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