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Stevens, Jon Scott; Gleitman, Lila R.; Trueswell, John C.; Yang, Charles – Cognitive Science, 2017
We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…
Descriptors: Semantics, Associative Learning, Probability, Computational Linguistics
Silberman, Yaron; Bentin, Shlomo; Miikkulainen, Risto – Cognitive Science, 2007
Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words…
Descriptors: Semantics, Schizophrenia, Associative Learning, Computational Linguistics