Semi Supervised Approach for Relation Extraction in Agriculture Documents-Reference-Cited by-同舟云学术

Semi Supervised Approach for Relation Extraction in Agriculture Documents

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 OITS International Conference on Information Technology (OCIT)
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Author:

G Veena¹,Gupta Deepa²,Kanjirangat Vani³

Affiliation:

1. Amrita Vishwa Vidyapeetham,Department of Computer Science and Applications,Amritapuri,India

2. Amrita Vishwa Vidyapeetham,Department of Computer Science and Applications,Bengaluru,India

3. Istituto Dalle Molle di Studi sull'lntelligenza Artificiale USI/SUPSI,Switzerland

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10053682/10053626/10053800.pdf?arnumber=10053800

Reference35 articles.

1. A Deep Learning-Based Named Entity Recognition in Biomedical Domain

2. Attention is all you need;vaswani;Advances in neural information processing systems,2017

3. A hybrid model based on neural networks for biomedical relation extraction

4. The AGROVOC Linked Dataset

5. Semi-supervised relation extraction with large-scale word clustering;sun;ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics Human Language Technologies,0

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1. NREE: Nested Relation Extraction in the Economic Field;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17

2. Semi-Supervised Bootstrapped Syntax-Semantics-Based Approach for Agriculture Relation Extraction for Knowledge Graph Creation and Reasoning;IEEE Access;2023