The nature of statistical learning theory
The nature of statistical learning theory
The String-to-String Correction Problem
Journal of the ACM (JACM)
Automatic acquisition of named entity tagged corpus from world wide web
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
Two-phase biomedical NE recognition based on SVMs
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
Boosting precision and recall of dictionary-based protein name recognition
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
Protein name tagging for biomedical annotation in text
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
The GENIA corpus: an annotated research abstract corpus in molecular biology domain
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Named entity recognition in Vietnamese using classifier voting
ACM Transactions on Asian Language Information Processing (TALIP)
| Hi-index | 0.00 |
In this paper, we propose two independent solutions to the problems of spelling variants and the lack of annotated corpus, which are the main difficulties in SVM(Support-Vector Machine) and other machine-learning based biological named entity recognition. To resolve the problem of spelling variants, we propose the use of edit-distance as a feature for SVM. To resolve the lack-of-corpus problem, we propose the use of virtual examples, by which the annotated corpus can be automatically expanded in a fast, efficient and easy way. The experimental results show that the introduction of edit-distance produces some improvements. And the model, which is trained with the corpus expanded by virtual examples, outperforms the model trained with the original corpus. Finally, we achieved the high performance of 71.46 % in F-measure (64.03 % in precision, 80.84 % in recall) in the experiment of five categories named entity recognition on GENIA corpus (version 3.0).