An intrinsic information content‐based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology
提出一种基于信息内容的本体概念语义相似度计算方法，引入不相交共同祖先这一新结构，在多个基准数据集上比现有方法更接近人类判断。
Finding similarity between concepts based on semantics has become a new trend in many applications (e.g., biomedical informatics, natural language processing). Measuring the Semantic Similarity (SS) with higher accuracy is a challenging task. In this context, the Information Content (IC)‐based SS measure has gained popularity over the others. The notion of IC evolves from the science of information theory. Information theory has very high potential to characterize the semantics of concepts. Designing an IC‐based SS framework comprises (i) an IC calculator, and (ii) an SS calculator. In this article, we propose a generic intrinsic IC‐based SS calculator. We also introduce here a new structural aspect of an ontology called DCS (Disjoint Common Subsumers) that plays a significant role in deciding the similarity between two concepts. We evaluated our proposed similarity calculator with the existing intrinsic IC‐based similarity calculators, as well as corpora‐dependent similarity calculators using several benchmark data sets. The experimental results show that the proposed similarity calculator produces a high correlation with human evaluation over the existing state‐of‐the‐art IC‐based similarity calculators.