Testing the cognitive relevance of a geometric model on a word association task a comparison of humans acom and lsa

The general aim of this study is to validate the cognitive relevance of the geometric model used in the semantic atlases (SA). With this goal in mind, we compare the results obtained by the automatic contexonym organizing model (ACOM)--an SA-derived model for word sense representation based on contextual links--with human subjects' responses on a word association task. We begin by positioning the geometric paradigm with respect to the hierarchical paradigm (WordNet) and the vector paradigm (latent semantic analysis [LSA] and the hyperspace analogue to language model). Then we compare ACOM's responses with Hirsh and Tree's (2001) word association norms based on the responses of two groups of subjects. The results showed that words associated by 50{\%} or more of the Hirsh and Tree subjects were also proposed by ACOM (e.g., 71{\%} of the words in the norms were also given by ACOM). Finally, we compare ACOM and LSA on the basis of the same association norms. The results indicate better performance for the geometric model.