计算机工程与应用2018，Vol.54Issue(5)：117-121,5.DOI:10.3778/j.issn.1002-8331.1609-0294
基于转移学习的中文命名实体识别
Chinese named entity recognition based on transformation learning
摘要
Abstract
Chinese named entity recognition is widely used in many important areas.To improve the precision and recall of recognition,a new algorithm for Chinese named entity recognition based on transformation learning is proposed in this paper. The central idea behind Transformation-Based Learning(TBL)is to start with some simple solution to the problem,and apply transformations at each step.The transformation which results in the largest benefit is selected and applied to the problem.The algorithm stops when the selected transformation does not modify the data in enough space. This paper puts forward a method to obtain the rule template and constraints file.According to this,a completed Chinese named entity recognition model is proposed.Using this model to experiment,the precision and recall of named entity recognition get a better result.关键词
命名实体识别/转移学习/准确率/召回率Key words
named entity recognition/transformation-based learning/precision/recall分类
信息技术与安全科学引用本文复制引用
周法国,吴锡坤,孙泰,孙镇..基于转移学习的中文命名实体识别[J].计算机工程与应用,2018,54(5):117-121,5.基金项目
国质检科技计划资助(No.2014QK111) （No.2014QK111）
中央高校基本科研业务费专项资金(No.2009QJ13) （No.2009QJ13）
国家科技支撑计划(No.2013BAK07B02). （No.2013BAK07B02）
