Chinese Organization Name Recognition Based on Co-training Algorithm | |
Ke Xiao ; Li Shaozi ; Li SZ(李绍滋) | |
2008 | |
英文摘要 | Conference Name:3rd International Conference on Intelligent System and Knowledge Engineering. Conference Address: Xiamen, PEOPLES R CHINA. Time:NOV 17-19, 2008.; Organization name recognition is the most difficult part in named entity recognition, in order to reduce the use of tagged corpus and use a large amount of untagged corpus, we firstly present using semi-supervised machine learning algorithm Co-training combining with conditional random fields model and support vector machines on Chinese organization name recognition. Based on the principles of compatible and uncorrelated, we construct different classifiers from different views of conditional random fields model, and also construct different classifiers from two models of conditional random fields model and support vector machines as two views. Then present a heuristic untagged samples selection algorithm. From the experimental results we can see that, under the same F-measure, Co-training algorithm simply use about 30% of the tagged data compared to single statistical model; under the same tagged data, Co-training algorithm has an F-measure increase about 10% than single statistical model. |
语种 | 英语 |
出处 | http://dx.doi.org/10.1109/ISKE.2008.4731034 |
出版者 | IEEE |
内容类型 | 其他 |
源URL | [http://dspace.xmu.edu.cn/handle/2288/86539] ![]() |
专题 | 信息技术-会议论文 |
推荐引用方式 GB/T 7714 | Ke Xiao,Li Shaozi,Li SZ. Chinese Organization Name Recognition Based on Co-training Algorithm. 2008-01-01. |
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