[1]邱莎[] 阿圆 王付艳 丁海燕.基于统计的中文地名自动识别研究[J].计算机技术与发展,2011,(11):35-38.
　QIU Sha,A Yuan,WANG Fu-yan,et al.Study on Automatic Recognition of Chinese Location Names Based on Statistical Method[J].,2011,(11):35-38.
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基于统计的中文地名自动识别研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2011年11期
页码:
35-38
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Study on Automatic Recognition of Chinese Location Names Based on Statistical Method
文章编号:
1673-629X（2011）11-0035-04
作者:
邱莎[1; 3] 阿圆1 王付艳1 丁海燕2
[1]昆明学院信息技术学院[2]云南大学信息学院[3]复旦大学计算机科学技术学院
Author(s):
QIU Sha;  A Yuan;  WANG Fu-yan;  DING Hai-yan
[1]Institute of Information Technology, Kunming University[2]Institute of Information, Yunnan University[3]Institute of Computer Science Technology, Fudan University
关键词:
中文地名识别; 条件随机场; 特征模板
Keywords:
Chinese location name recognition;  conditional random fields（CRFs） ;  feature template
分类号:
TP31
文献标志码:
A
摘要:
中文地名的自动识别是命名实体识别任务中难度较大的任务之一，目的是从中文文本中自动准确提取地理专用名词。文中使用统计模型中的条件随机场对中文地名的自动识别在字一级粒度进行了研究。在研究中利用条件随机场能任意添加特征的优点，合理引用了丰富的特征组合，在大规模语料上进行训练，统计获得标注序列基于特征集的条件概率分布，并采用序列标注的方式，实现中文地名的自动识别。多次闭合测试和开放测试结果Fl值为90％左右，识别效果良好
Abstract:
Chinese location name recognition is one of the difficult tasks of Chinese named entity recognition. Its task is automatic extracting geography special nouns from Chinese texts accurately. Based on one of the statistical models, the conditional random fields, discussed the task of automatic recognition of Chinese location name on the character level. To take advantage of the ability of using arbi- trary features as input in CRFs, not only reasonable feature template was structured, but also the large scale corpus was used in training. The conditional probability distribution of label sequences was computed using statistics. By sequence labeling, it implemented the automatic recognition of Chinese location name. It obtained promising results on different closed and opened test corpus with the F1 measurement value of about 90%

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备注/Memo

备注/Memo:
云南省教育科研资助项目（09Y0047）;昆明学院科研课题基金（2009c012）邱莎（1974-），女，云南曲靖人，硕士，讲师，复旦大学访问学者，研究方向为自然语言处理
更新日期/Last Update: 1900-01-01