Implementing Semantic Networks in an Electronic Neural Network

Author(s):  
Yuzo Hirai ◽  
Qing Ma
2000 ◽  
Vol 6 (5) ◽  
pp. 608-619 ◽  
Author(s):  
AMIR B. GEVA ◽  
AVI PELED

A neural network model with dynamic thresholds, asymmetric connections, and clustered memories simulates spread activation that is hypothesized for semantic networks in the brain. By altering the parameters of the dynamic threshold a large range of disturbances can be generated in the model. These disturbances show metaphorical resemblance to certain general clinical descriptions of mental disturbances found in psychiatric patients engaged in various cognitive tasks. Even though the model is highly theoretical and metaphoric, it may help to gain certain insights into the relation between alterations of certain neural parameters, for example, thresholds and connectivity, and clinical symptoms in patients. (JINS, 2000, 6, 608–619.)


2017 ◽  
Vol 7 (4) ◽  
pp. 229-242 ◽  
Author(s):  
Yuanzhi Ke ◽  
Masafumi Hagiwara

Abstract In this paper, a novel neural network is proposed, which can automatically learn and recall contents from texts, and answer questions about the contents in either a large corpus or a short piece of text. The proposed neural network combines parse trees, semantic networks, and inference models. It contains layers corresponding to sentences, clauses, phrases, words and synonym sets. The neurons in the phrase-layer and the word-layer are labeled with their part-of-speeches and their semantic roles. The proposed neural network is automatically organized to represent the contents in a given text. Its carefully designed structure and algorithms make it able to take advantage of the labels and neurons of synonym sets to build the relationship between the sentences about similar things. The experiments show that the proposed neural network with the labels and the synonym sets has the better performance than the others that do not have the labels or the synonym sets while the other parts and the algorithms are the same. The proposed neural network also shows its ability to tolerate noise, to answer factoid questions, and to solve single-choice questions in an exercise book for non-native English learners in the experiments.


2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  

1984 ◽  
Vol 96 (2) ◽  
pp. 292-315 ◽  
Author(s):  
P. N. Johnson-Laird ◽  
D. J. Herrmann ◽  
R. Chaffin
Keyword(s):  

2014 ◽  
Author(s):  
John Powell Taylor ◽  
Shanna'le Ashworth ◽  
Matthew Fischer ◽  
Kadie Skou ◽  
Almyra Perry

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