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- Title
Recognition of Chinese Organization Name Using Co-training.
- Authors
Ke Xiao; Li Shao-zi; Chen Jin-xiu
- Abstract
Chinese organization name recognition is hard and important in natural language processing. To reduce tagged corpus and use untagged corpus, we presented combing Co-training with support vector machines (SVM) and conditional random fields (CRF) to improve recognition results. Based on principles of uncorrelated and compatible, we constructed different classifiers from different views within SVM or CRF alone and combination of these two models. And we modified a heuristic untagged samples selection algorithm to reduce time complexity. Experimental results show that under the same tagged data, Co-training has 10% F-measure higher than using SVM or CRF alone; under the same F-measure, Co-training saves at most 70% of tagged data to achieve the same performance.
- Subjects
CHINESE people; CHINESE language; NATURAL language processing; SUPPORT vector machines; RANDOM fields
- Publication
Journal of Donghua University (English Edition), 2010, Vol 27, Issue 2, p193
- ISSN
1672-5220
- Publication type
Article