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基于条件随机域的生物命名实体识别 被引量：17

Biological Named Entity Recognition Based on Conditional Random Fields
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摘要 提出一种基于条件随机域模型的生物命名实体识别方法,结合单词构词特性以及距离依赖特性,在JNLPBA的GENIAV3.02数据上进行实验,测试结果表明,引入距离依赖后,系统的识别性能比只利用单特性的条件随机域方法提高2.54%,可获得较好的识别效果,提高了系统的识别效率。 A biological named entity recognition method based on Conditional Random Fields（CRF） is proposed, which combines the word characteristics and the distance between words. Experiments are carried out with GENIAV3.02 datasets given by JNLPBA. Experimental results show that, after introducing words distance characteristics, the proposed method can achieve a performance improvement of 2.54% compared to simple conditional random fields, therefore achieving a better recognition result and improve the efficiency of systems.
作者 彭春艳 张晖 包玲玉 陈昌平
机构地区 西南科技大学计算机科学与技术学院
出处 《计算机工程》 CAS CSCD 北大核心 2009年第22期197-199,共3页 Computer Engineering
基金 国家"863"计划基金资助项目(2007AA01Z151) 国家人事部留学归国人员择优基金资助项目 西南科技大学博士科研基金资助项目(2007011022)
关键词 生物命名实体识别 条件随机域 隐马尔科夫模型 biological named entity recognition Conditional Random Fields（CRF） Hidden Markov Models（HMM）
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献5

  • 1Lafferty J, McCallum A, Pereira F. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data[C]//Proc. of the 18th International Conference on Machine Learning. Williamstown, Australia: [s. n.], 2001.
  • 2Friedrich C M, Revillion T, Hofmann M, et al. Biomedical and Chemical Named Entity Recognition with Conditional Random Fields: The Advantage of Dictionary Features[C]//Proc. of the 2nd International Symposium on Semantic Mining in Biomedicine. Jena, Germany: [s. n.], 2006.
  • 3Wellner B, McCallum A, Peng Fuchun, et al. An Integrated, Conditional Model of Information Extraction and Coreference with Application to Citation Graph Construction[C]//Proc. of the 20th Conference on Uncertainty in Artificial Intelligence. Banff, Canada:[s. n.], 2004.
  • 4杨志豪,林鸿飞,李彦鹏.条件随机域与上下文线索结合的生物实体识别[J].计算机工程,2008,34(7):203-204. 被引量：3
  • 5朱鸿宇,刘瑰,陈左宁,唐福华.实体关系识别中长距离依赖问题的研究[J].小型微型计算机系统,2008,29(2):364-367. 被引量：2

二级参考文献14

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计算机工程
2009年 第22期

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