Using Information Content to Evaluate Semantic Similarity in a Taxonomy
Using Information Content to Evaluate Semantic Similarity in a Taxonomy
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发表时间：
1995-08
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通讯作者：
P. Resnik
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作者：
P. Resnik
本文基于信息内容的概念，提出了IS-A分类中一种新的语义相似性度量方法。实验评估表明，该方法执行得很好(与人类相似性判断基准集的相关性为r=0.79，执行相同任务的人类受试者的上界为r=0.90)，并且显著优于传统的边缘计数方法(r=0.66)。
This paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content. Experimental evaluation suggests that the measure performs encouragingly well (a correlation of r = 0.79 with a benchmark set of human similarity judgments, with an upper bound of r = 0.90 for human subjects performing the same task), and significantly better than the traditional edge counting approach (r = 0.66).