Enhancing HMM-based biomedical named entity recognition by studying special phenomena-Reference-Cited by-同舟云学术

Enhancing HMM-based biomedical named entity recognition by studying special phenomena

Published:2004-12 Issue:6 Volume:37 Page:411-422
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Zhang Jie,Shen Dan,Zhou Guodong,Su Jian,Tan Chew-Lim

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference20 articles.

1. Zhou GD, Su J. Named Entity Recognition using an HMM-based Chunk Tagger. In: Proceedings of the 40th annual meeting of the association for computational linguistics (ACL); 2002. p. 473–80

2. Bikel M, Schwartz Danie R, Weischedel Ralph M. An algorithm that learns what’s in a name. In: Proceedings of machine learning; 1999 [Special Issue on NLP]

3. Borthwick A. A maximum entropy approach to named entity recognition. Ph.D. thesis. New York University

4. Kazama J, Makino T, Ohta Y, Tsujii J. Tuning support vector machines for biomedical named entity recognition. In: Proceedings of the workshop on natural language processing in the biomedical domain; 2002 (at ACL’2002). p. 1–8

5. Takeuchi K, Collier N. Use of support vector machines in extended named entity recognition. In: Proceedings of the sixth conference on natural language learning (CONLL 2002); 2002. p. 119–25

Cited by 59 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Camouflaged named entity recognition in 2D sentence representation;Expert Systems with Applications;2024-12

2. Based on BERT-wwm for Agricultural Named Entity Recognition;Agronomy;2024-06-04

3. Biomedical named entity recognition based on multi-cross attention feature fusion;PLOS ONE;2024-05-28

4. Research on medical text named entity recognition based on Two-stage approach;Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy;2024-03

5. Named Entity Recognition in Government Audit Texts Based on ChineseBERT and Character-Word Fusion;Applied Sciences;2024-02-09