The Optimal Sampling Strategy for Few-shot Named Entity Recognition Based with Prototypical Network-Reference-Cited by-同舟云学术

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The Optimal Sampling Strategy for Few-shot Named Entity Recognition Based with Prototypical Network

Published:2024-06-30 Issue: Volume:32 Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
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Author:

Chen Junqi¹,Ding Zhaoyun¹,Jin Guang²,Yang Guoli³

Affiliation:

1. National University of Defense Technology,National Key Laboratory of Information Systems Engineering,Changsha,China

2. National University of Defense Technology,College of Systems Engineering,Changsha,China

3. Academy of Military Sciences,Institute of Systems Engineering,Beijing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10649912.pdf?arnumber=10649912

Reference38 articles.

1. Open-domain extraction of future events from Twitter

2. Extracting company names from text

3. Unsupervised models for named entity classification;Collins

4. Statistical named entity recognizer adaptation

5. A hybrid approach to NER by MEMM and manual rules

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