correlated properties and computing word meaning

[Ken McRae]

The following paper is now available in the connectionist archive,
archive.cis.ohio-state.edu (128.146.8.52), in pub/neuroprose under the name
mcrae.corredprops.ps.Z



     The Role of Correlated Properties in Accessing Conceptual Memory


                                 Ken McRae
                               Virginia de Sa
                    University of Rochester, Rochester, NY

                             Mark S. Seidenberg
              University of Southern California, Los Angeles, CA


keywords:  correlated properties, conceptual memory, word meaning,
           connectionist models, semantic priming




                                ABSTRACT
A fundamental question in research on conceptual structure concerns how 
information is represented in memory and used in tasks such as 
recognizing words.  The present research focused on the role of 
correlations among semantic properties in conceptual memory.  Norms 
were collected for 190 entities from 10 categories.  Property 
intercorrelations were shown to influence people's performance in both a 
property verification task and a short interval semantic priming experiment.  
Furthermore, correlated properties were more important for biological 
kinds than for artifacts.  A connectionist model of the computation of word 
meaning was implemented in which property intercorrelations developed 
in the course of learning.  The model was used to simulate the results of 
the two experiments.  We then tested a novel prediction derived from the 
model:  that the intercorrelational density of a concept's properties should 
influence the speed with which a concept is computed.  This prediction was 
confirmed in a final experiment.  We concluded that encoded knowledge of 
property co-occurrences plays a prominent role in the representation and 
computation of word meaning.