  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).
