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Semantic neural network

Semantic neural network (SNN) is based on John von Neumann's neural network [von Neumann, 1966] and Nikolai Amosov M-Network. There are limitations… 
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Related topics

Related topics

4 relations
Computational creativityOutline of natural language processingSemantic network

Broader (1)

Natural language processing

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
A Neural Network Component for Knowledge-Based Semantic Representations of Text
This paper presents Semantic Neural Networks (SNNs), a knowledge-aware component based on deep learning. SNNs can be trained to… 
2012
2012
A Security Control Model of Semantic Neural Network Based on Concept Description
This paper proposes a new security model in Semantic Neural Network. A Semantic Neural Network (SNN) is a semantics network… 
2009
2009
Self-organizing content management with semantic neural networks
Semantic neural networks, as knowledge representations, are relatively extensible and they can be used to model the… 
2009
2009
Dealing with written language semantics by a connectionist model of cognitive reading
2009
2009
Teachable characters: semantic neural networks in game AI
The aim of the study was to apply machine learning into educational game and evaluate the outcome in context of cognitive… 
2009
2009
Assessing aspects of reading by a connectionist model
2007
2007
Semantic Neural Networks and the Deep-Seated Semantic Computing of the Natural Language
In this paper, we present the formalized definition of Semantic Neural Network, the neurons in it and the deep semantic computing… 
2003
2003
Neural network based adaptive optimal controller on optimization models
When the future information for an optimization model is not complete, the model tends to incorporate such uncertainties as some… 
2001
2001
The Structure of a Semantic Neural Network Extracting the Meaning from a Text
A clocked linear tree is considered as the structure of connections between neurons of a semantic neural network that can extract… 
1996
1996
Detection of contradictions in a semantic neural network
Connectionism is one of several models that explain how the brain might encode information. It implies that any cognizable entity… 
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