Which statistics reflect semantics? Rethinking synonymy and word similarity

A great deal of work has been done of late on the statistical modeling of word similarity relations (cf.Schütze (1992), Lund and Burgess (1996) Landauer and Dumais (1997), Lin (1998), Turney (2001)). While this has largely been viewed as an engineering task (with the notable exception of much writing on Latent Semantic Analysis (LSA)), the relative success of different approaches to constructing word similarity measures is highly relevant to issues in theoretical semantics and language acquisition. With this background in mind, this paper has two main aims. First, we will present yet another statistical approach to the calculation of word-similarity scores (LC-IR), which significantly outperforms other methods on standard benchmarks including the 80-question set of TOEFL® synonym test items first employed by Landauer and Dumais (1997).1 Second, we hope to demonstrate that