NDLI: An attractor neural network model of semantic fact retrieval

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International 1989 Joint Conference on Neural Networks

An attractor neural network model of semantic fact retrieval

Content Provider	IEEE Xplore Digital Library
Author	Usher, M. Ruppin, E.
Copyright Year	1990
Abstract	Presents an attractor neural network model of semantic fact retrieval based on A.M. Collins and M.R. Quillian's (1969) semantic network models. In the context of modeling a semantic network, a distinction is made between associations linking together objects belonging to hierarchically related semantic classes and associations linking together objects and their attributes. Using a distributed representation leads to some generalization properties that have computational advantage. Simulations demonstrate that it is feasible to get reasonable response performance regarding various semantic queries and that the temporal pattern of retrieval times obtained in simulations is consistent with psychological experimental data. Therefore, it is shown that attractor neural networks can be successfully used to model higher-level cognitive phenomena than those modeled by standard content-addressable pattern recognition
Starting Page	683
Ending Page	688
File Size	497026
Page Count	6
File Format	PDF
DOI	10.1109/IJCNN.1990.137917
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article

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