Title :
Categorical Mapping from Ontology to Neural Network: Initial Studies of Simple Neural Networks´ Concept Capacity
Author :
Taylor, Shawn E. ; Healy, Michael J. ; Caudell, Thomas P.
Author_Institution :
Univ. of New Mexico, Albuquerque
Abstract :
A recent neural network semantic theory provides the framework for mapping ontologies to neural networks. We use category theory, the mathematical theory of structure, to explore the concept representational abilities of select neural networks. Methodologies suggested by the semantic theory have been gainfully applied to specific applications. This paper describes a rigorous and numerical study of the implementation of neural category representations into an actual neural network.
Keywords :
neural nets; ontologies (artificial intelligence); categorical mapping; mathematical theory of structure; neural network semantic theory; ontology; Artificial neural networks; Biological neural networks; Data mining; Feature extraction; Grounding; Leg; Neural networks; Neurons; Neuroscience; Ontologies;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371269