计算机工程与应用2016，Vol.52Issue(19)：140-145,6.DOI:10.3778/j.issn.1002-8331.1602-0056
基于领域相关性度量的抑郁症药物概念抽取
Concepts extraction of depression drug based on domain correlation measure
摘要
Abstract
It has a significant guiding significance for developing intelligent auxiliary diagnosis and treatment of depres-sion to develop automatically ontology learning technology of depression drug ontology based on mass biomedicine litera-tures. Concepts extraction has an effect on learning relations and axioms, and then decides the quality of ontology learning. However, existing algorithms are only suitable for general fields, not for special and fine grit fields. This paper proposes a method of concepts extraction from depression drug field, which employs log-likelihood ratio and domain correlation function based on traditional domain relevance and domain consensus. The experimental results show that the method can reduce the impact on concepts extraction caused by other related fields of depression, and improve the calculation of domain membership degree for low-frequency terms. Compared with others, the precise and recall has been greatly improved.关键词
本体学习/概念抽取/抑郁症/对数似然比/领域关联函数Key words
ontology learning/concepts extraction/depression/log-likelihood ratio/domain correlation function分类
信息技术与安全科学引用本文复制引用
王宁宁,陈建辉..基于领域相关性度量的抑郁症药物概念抽取[J].计算机工程与应用,2016,52(19):140-145,6.基金项目
国家重点基础研究发展规划项目（973）（No.2014CB744600）；国家自然科学基金（No.61272345）。 （）
