A connectionist simulation of human word associations

Summary form only given, as follows. On the basis of the frequencies and co-occurrences of words in large bodies of text, autoassociative lexical nets which describe the connective weights between 371 words were computed. These nets were used to predict the free associative responses of the word association norms collected by Russel and Jenkins from college students. Different assumptions about the learning of the connective weights, the influence of word order, and the generation of associative responses were compared. It was shown quantitatively that there is a high level of correspondence between the present predictions and the experimental data.<
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