A semantic similarity approach combining location and intrinsic information content

摘要：

To measure semantic similarity between terms is an important issue in many research fields. In this paper, a new semantic similarity approach, which combines the intrinsic information content of the term and the location of the term in the directed acyclic graph, is presented. The approach first calculates the sub graphs of two terms based the directed acyclic graph, and then calculates the intersection and union of the sub graphs. The semantic similarity of two terms is the ratio of the total intrinsic information content of terms in the intersection to the total intrinsic information content of terms in the union. Experimental evaluations using MeSH biomedical ontology indicate that the proposed approach yields results that correlate more closely with human assessments than other.

关键词： semantic similarity intrinsic information content MeSH DAG

作者: Wei Wei Yang Xiang Qian Chen

作者单位: College of Electronics and Information Engineering Tongji University Shanghai, China School of Infor College of Electronics and Information Engineering Tongji University Shanghai. China College of Electronics and Information Engineering Tongji University Shanghai, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 215-218

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）