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现代图书情报技术  2015, Vol. 31 Issue (12): 57-64    DOI: 10.11925/infotech.1003-3513.2015.12.09
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于医学本体的术语相似度算法研究
范雪雪1, 王志荣1, 徐晤1, 梁银2, 马小虎3
1 徐州医学院临床学院 徐州 221004;
2 江苏师范大学计算机科学与技术学院 徐州 221116;
3 苏州大学计算机科学与技术学院 苏州 215006
Research on Semantic Similarity Estimation Algorithm of Medical Terminology Based on Medical Ontology
Fan Xuexue1, Wang Zhirong1, Xu Wu1, Liang Yin2, Ma Xiaohu3
1 Clinical Medical School, Xuzhou Medical College, Xuzhou 221004, China;
2 School of Computer Science and Technology, Jiangsu Normal University, Xuzhou 221116, China;
3 School of Computer Science and Technology, Soochow University, Suzhou 215006, China
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摘要 

[目的]借助大型的医学本体, 提升医学术语相似度计算精度。[方法]依据SNOMED CT和MeSH两个医学本体的层级结构和语义关系, 提取概念术语的深度、距离等语义参数, 并用概念密度对其加权得到深度系数和距离系数, 构造相似度函数进行术语相似度计算。[结果]该算法能在两个医学本体中进行术语相似度计算, 较传统算法更加接近人工评分标准。[局限]该方法较为依赖本体结构。[结论]该方法能够提高以医学本体为基础的术语相似度计算精确度。

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Abstract

[Objective] Based on the comprehensive medical Ontologies, this paper proposes a new algorithm to enhance the precision of semantic similarity estimation of medical terminology. [Methods] On the basis of the hierarchy and semantic relationships of concepts of SNOMED CT and MeSH, the semantic parameters such as depth and distance are extracted. Then the depth factor and the distance factor are obtained weighted by the concept density, and the function of semantic similarity is thus established. [Results] The algorithm is applicable to both distinctive medical Ontologies, and the experimental results demonstrate that this algorithm has higher correlation coefficient with manual scoring versus conventional algorithms. [Limitations] This algorithm is subject to hierarchy of Ontologies. [Conclusions] The new algorithm benefits the enhanced precision of semantic similarity estimation of medical terminology.

收稿日期: 2015-05-28     
:  TP391  
  G35  
基金资助:

本文系江苏省现代教育技术研究课题“智能无纸化医学考试系统的开发”(项目编号:19696)和徐州医学院科研课题“基于SNOMED CT的医学术语相似度计算研究”(项目编号:2014KJ31)的研究成果之一。

通讯作者: 范雪雪, ORCID: 0000-0002-0450-480X, E-mail: xuexuefx@126.com。     E-mail: xuexuefx@126.com
作者简介: 作者贡献声明:范雪雪: 提出研究思路, 设计并实现算法, 撰写论文; 王志荣, 徐晤: 提供实验数据, 进行数据分析; 梁银: 数据分析, 论文修订; 马小虎: 论文修订。
引用本文:   
范雪雪, 王志荣, 徐晤, 梁银, 马小虎. 基于医学本体的术语相似度算法研究[J]. 现代图书情报技术, 2015, 31(12): 57-64.
Fan Xuexue, Wang Zhirong, Xu Wu, Liang Yin, Ma Xiaohu. Research on Semantic Similarity Estimation Algorithm of Medical Terminology Based on Medical Ontology. New Technology of Library and Information Service, DOI:10.11925/infotech.1003-3513.2015.12.09.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2015.12.09

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