基于朴素贝叶斯的中国人姓名识别

Hui Zeng, J. Wang, Tao Wan
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引用次数: 1

摘要

在传统的单纯考虑人名特征的朴素贝叶斯分类算法的基础上,引入人名上下边界词。为了克服边界定义的困难,我们统计了标注语料库中中文名称的字符频率和边界模板的频率。然后使用这些识别的人名来匹配文本中遗漏的事件。该方法简便,效果良好。实验结果表明,该方法提高了人名识别的f值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chinese Person Name Recognition Based on Naive Bayes
On the basis of the traditional Naive Bayesian classification algorithm that just considered character of Chinese person name, we brought person name's up and down boundary words in it. In order to overcome the difficulty of boundary defining, we counted Chinese name's character frequency and boundary templates' frequency from tagged corpus. Then these recognized person names are used to match the missed occurrence in the text. The method is easy and the final result is good. Experimental results show that the F-value for recognition of Chinese person name was increased.
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