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
[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.
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.
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