RAN: A Relation-aware Network for Relation Extraction-Reference-Cited by-同舟云学术

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RAN: A Relation-aware Network for Relation Extraction

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Li Yile¹,Gu Xiaoyan²,Yue Yinliang³,Wang Zhuo⁴,Li Bo²,Wang Weiping²

Affiliation:

1. Institute of Information Engineering, Chinese Academy of Sciences, School of Cyber Security, University of Chinese Academy of Sciences,Beijing,China

2. Institute of Information Engineering, Chinese Academy of Sciences,Beijing,China

3. Zhongguancun Laboratory,Beijing,China

4. Sangfor Inc.,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191909.pdf?arnumber=10191909

Reference30 articles.

1. Modeling Multi-Granularity Hierarchical Features for Relation Extraction

2. End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures

3. The Stanford CoreNLP Natural Language Processing Toolkit

4. Position-aware Attention and Supervised Data Improve Slot Filling

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