Resnik, PhilipDiab, MonaThe way we model semantic similarity is closely tied to our understanding of linguistic representations. We present several models of semantic similarity, based on differing representational assumptions, and investigate their properties via comparison with human ratings of verb similarity. The results offer insight into the bases for human similarity judgments and provide a testbed for further investigation of the interactions among syn tactic properties, semantic structure, and semantic con tent. (Also cross-referenced as UMIACS-TR-2000-40, LAMP-TR-047)en-USMeasuring Verb SimilarityTechnical Report