%A Duan Yufeng, Zhu Wenjing, Chen Qiao, Cui Hong %T Semantic Annotation of Species Description Text in Chinese by Combining Naïve Bayes Algorithm with Bootstrapping Method %0 Journal Article %D 2014 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.1003-3513.2014.05.11 %P 83-89 %V 30 %N 5 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_3902.shtml} %8 2014-05-25 %X

[Objective] To reduce cost of machine learning by declining the size of learning dataset in species description text annotation in Chinese. [Methods] Based on Bootstrapping method, design a weakly supervised learning method which performs learning and tagging processes iteratively with a small amount of data at the beginning. The iteration process promotes annotation ability continuously by expanding the knowledge base. [Results] The average score of F-value runs up to 0.911 2 on a dataset with 15 041 sentences. [Limitations] The annotation efficiency might be relatively low on sparse data. [Conclusions] The experimental data shows that the algorithm in this study not only declines the dataset size requirement of machine learning dramatically, but also increases annotation efficiency.