Learning refined features for open-world text classification with class description and commonsense knowledge
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Software
Link
https://link.springer.com/content/pdf/10.1007/s11280-022-01102-6.pdf
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3. Wu, X., Cai, Y., Li, Q., Xu, J., Leung, H.-F.: Combining weighted category-aware contextual information in convolutional neural networks for text classification. World Wide Web 23(5), 2815–2834 (2020)
4. 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)
5. Li, Z., Cai, Y., Tan, X., Han, G., Ren, H., Wu, X., Li, W.: Learning refined features for open-world text classification. In: Asia-Pacific Web (APWeb) and Web-Age information management (WAIM) Joint international conference on Web and Big Data, pp. 367–381. Springer (2021)
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