By TIMOTHY P. McNAMARA
I used to be trying to find a e-book reviewing the literature on semantic priming and was once tremendous inspired with this e-book. it's concise and densely choked with info. even as, McNamara writes super essentially.
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Additional info for Semantic Priming: Perspectives from Memory and Word Recognition
This network learns to associate written words with their meanings. fm Page 33 Monday, June 20, 2005 11:33 AM Chapter 5: Distributed Network Models 33 is represented by a pattern of activation over a set of semantic units. , dog-cat). , dogs and goats are both mammals). The categorical relatedness between two words is encoded by the degree of feature overlap between their semantic representations. , dachshund). Associative relatedness is determined by the frequency with which one word follows another during learning.
The weights on the connections between units are then modified so as to improve the match between the actual activations of the semantic units and the assigned semantic representation for the word. Selection of the next word for training can be random or determined by such variables as word frequency and associative relatedness. For instance, in the application discussed by Plaut (1995), each word was assigned, before training, one associate, which was semantically unrelated. Associations were unidirectional; that is, no two words were each other’s associate.
Becker’s verification model shares many features with Anderson’s (1983a) model of semantic priming in lexical decision (of course, Becker’s model preceded Anderson’s model historically). Generation of the sensory set is similar to the identification of the similar word, except that the sensory set contains many candidates, whereas only one similar word is identified. Both models employ a verification process in which candidates are compared to the visual stimulus. The major differences exist in the explanation of facilitation in semantic priming.
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