一种基于肝炎本体的语义查询扩展系统方法。
An approach to semantic query expansion system based on Hepatitis ontology.
作者信息
Yunzhi Chen, Huijuan Lu, Shapiro Linda, Travillian Ravensara S, Lanjuan Li
机构信息
Zhejiang University School of Medicine, Hangzhou, China ; Hangzhou Vocational and Technical College, Hangzhou, China.
College of Information Engineering of China Jiliang University, Hangzhou, China.
出版信息
J Biol Res (Thessalon). 2016 Jul 4;23(Suppl 1):11. doi: 10.1186/s40709-016-0044-9. eCollection 2016 May.
BACKGROUND
Ontology development, as an increasingly practical vehicle applied in various fields, plays a significant role in knowledge management. This paper, focusing on constructing and querying a hepatitis ontology, aims to provide a framework for ontology-based medical services. The paper is devoted to the algorithm of query expansion for the hepatitis ontology, including synonym expansion, hypernym/hyponym expansion and expansion of similar words. It applies semantic similarity calculation to judge the similarity of retrieval terms.
RESULTS
The paper proposes a new prototype system. The accuracy of query expansion is improved in both precision@40 and AP@40, which indicates that query expansion improves the accuracy of the query after using the method proposed in this paper.
CONCLUSIONS
The paper has adopted semantic similarity computing to improve retrieval performance. Experiments show that search precision of query expansion is higher based on domain concept relationship.
背景
本体开发作为一种在各个领域中应用日益广泛的实用工具，在知识管理中发挥着重要作用。本文聚焦于构建和查询肝炎本体，旨在提供一个基于本体的医疗服务框架。本文致力于肝炎本体的查询扩展算法，包括同义词扩展、上位词/下位词扩展以及相似词扩展。它应用语义相似度计算来判断检索词的相似度。
结果
本文提出了一个新的原型系统。在精确率@40和平均准确率@40方面，查询扩展的准确率均有所提高，这表明使用本文提出的方法后，查询扩展提高了查询的准确性。
结论
本文采用语义相似度计算来提高检索性能。实验表明，基于领域概念关系的查询扩展搜索精度更高。
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