Meaning and the mental lexicon

This paper presents a network model of the mental lexicon and its formation. Models of word meaning typically postulate a network of nodes with connection strengths, of distances, that reflect semantic similarity, but seldom explain how the network is formed or how it could be represented in the brain. The model presented here is an attempt to address these questions. The network organizes semantically similar words into clusters when exposed to sequentially presented test. Lexical co-occurrence information is calculated and used to create a hierarchical semantic representation. The output is similar to semantic networks first described by [Collins and Loftus, 1975], but is created automatically.