The paper defines a similarity score S* that subtracts a contradiction ratio from a shared-property ratio, and organizes knowledge entities into threshold-based paraconsistent super-categories.
Using Information Content to Evaluate Semantic Similarity in a Taxonomy
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abstract
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).
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Un cadre paraconsistant pour l'{\'e}valuation de similarit{\'e} dans les bases de connaissances
The paper defines a similarity score S* that subtracts a contradiction ratio from a shared-property ratio, and organizes knowledge entities into threshold-based paraconsistent super-categories.