| 基于位置降噪和丰富语义的电子病历实体关系抽取 |
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| 引用本文： | 李丽双,袁光辉,刘晗喆.基于位置降噪和丰富语义的电子病历实体关系抽取[J].中文信息学报,2021,35(8):89-97. |
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| 作者姓名： | 李丽双 袁光辉 刘晗喆 |
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| 作者单位： | 1.大连理工大学 计算机科学与技术学院,辽宁 大连116024;
2.辽宁省肿瘤医院(中国医科大学肿瘤医院) 重症医学科,辽宁 沈阳 110042 |
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| 基金项目： | 大连市科技创新基金(2020JJ26GX035);国家自然科学基金(62076048, 61672126) |
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| 摘 要： | 当前的电子病历实体关系抽取方法存在两个问题: 忽视了位置向量噪声和语义表示匮乏。该文提出一种基于位置降噪和丰富语义的实体关系抽取模型。模型首先利用位置信息和专业领域语料训练的词向量信息获取每个词的注意力权重,然后将此权重与通用领域语料训练的词向量结合,实现位置向量降噪和丰富语义引入,最后根据加权后的词向量判断实体关系类型。该方法在2010年i2B2/VA语料上进行实验评估,F1值为76.47%,取得了基于该语料的最优结果。
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| 关 键 词： | 关系抽取 电子病历 位置向量降噪 丰富语义 |
| 收稿时间： | 2021-01-21 |
Entity Relationship Extraction from Electronic Medical Records Based on Location Noise Reduction and Rich Semantics |
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| LI Lishuang,YUAN Guanghui,LIU Hanzhe.Entity Relationship Extraction from Electronic Medical Records Based on Location Noise Reduction and Rich Semantics[J].Journal of Chinese Information Processing,2021,35(8):89-97. |
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| Authors: | LI Lishuang YUAN Guanghui LIU Hanzhe |
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| Affiliation: | 1.School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China;2.Department of Critical Care, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning 110042, China |
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| Abstract: | The present methods of entity relationship extraction are challenged by the noise of position vector and the lack of semantic representation. This paper proposed an entity relationship extraction model via both location based noise reduction and rich semantics. First, the model uses the position information and the word vector information trained by domain corpus to obtain the attention weight of each word.Then this weight is combined with the word vector trained by general field corpus to realize the noise reduction of position vector and the introduction of rich semantic information. Finally, the type of the entity relationship is determined by the weighted word vector. Evaluated on the i2B2 /VA corpus in 2010, experiments demonstrate a 76.47% F1 value, the best result on this corpus at present. |
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| Keywords: | relation extraction electronic medical records position vector noise reduction rich semantics |
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