| 基于实体词典与机器学习的基因命名实体识别 |
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| 引用本文： | 夏光辉,李军莲,阮学平.基于实体词典与机器学习的基因命名实体识别[J].医学信息学杂志,2015,36(12):54-60. |
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| 作者姓名： | 夏光辉 李军莲 阮学平 |
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| 作者单位： | 中国医学科学院医学信息研究所 北京 100020;中国医学科学院医学信息研究所 北京 100020;中国医学科学院医学信息研究所 北京 100020 |
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| 基金项目： | 国家科技支撑计划项目(项目编号:2011BAH10B05)。 |
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| 摘 要： | 将实体词典以特征的形式引入到机器学习模型中,提出一种基于实体词典与机器学习的基因命名实体识别方法,在GENIA 3.02语料上进行实验。测试结果表明引入实体词典特征后,在获得较高实体识别准确率的同时,优化CRFs识别模型的时间复杂度,提高系统识别效率。
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| 关 键 词： | 实体词典 机器学习 基因命名实体 命名实体识别 |
| 收稿时间： | 2015/11/13 0:00:00 |
Gene Named Entity Recognition Based on Entity Dictionary and Machine Learning |
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| XIA Guang-hui,LI Jun-lian and RUAN Xue-ping.Gene Named Entity Recognition Based on Entity Dictionary and Machine Learning[J].Journal of Medical Informatics,2015,36(12):54-60. |
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| Authors: | XIA Guang-hui LI Jun-lian and RUAN Xue-ping |
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| Institution: | Institute of Medial Information, Chinese Academy of Medical Sciences, Beijing 100020, China;Institute of Medial Information, Chinese Academy of Medical Sciences, Beijing 100020, China;Institute of Medial Information, Chinese Academy of Medical Sciences, Beijing 100020, China |
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| Abstract: | By introducing the entity dictionary into the model of machine learning in the form of characteristics,this article proposes a method of gene-named entity recognition based on entity dictionary and machine learning and experiments on corpus GENIT 3.02.As indicated by the test results,after the characteristics of the entity dictionary are introduced,while a higher accuracy rate of entity recognition is obtained,the time complexity of CRFs recognition model is optimized and the system's recognition efficiency is enhanced. |
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| Keywords: | Entity dictionary Machine learning Gene named entity Named entity recognition |
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