Title :
Evolving knowledge cells in the hierarchical associative memory
Author_Institution :
Dept. of Comput. Software, YongIn SongDara Coll., South Korea
Abstract :
For the purpose of building an intelligent knowledge system which is more adaptable to the dynamic environment, it is very important to design the knowledge system first of all. It is also necessary to introduce the new methodology as a life paradigm of generation, growing, forgetting and dying. We propose the evolving associative knowledge system as a model of an intelligent knowledge system with evolving knowledge cells in its hierarchical associative memory. It has the function of adaptive learning, selective processing, perception, inference and data extraction. Using the intelligent structure, this system evolves the knowledge cells according to DNA meta code as a life paradigm. This model is applied to the medical area and tested with symptom data
Keywords :
content-addressable storage; inference mechanisms; knowledge acquisition; knowledge based systems; learning systems; medical diagnostic computing; DNA meta code; adaptive learn; data extraction; dying; dynamic environment; evolving associative knowledge system; evolving knowledge cells; forgetting; generation; growing; hierarchical associative memory; inference; intelligent knowledge system; life paradigm; perception; selective processing; symptom data; Associative memory; Buildings; DNA; Data mining; Educational institutions; Humans; Intelligent structures; Intelligent systems; Knowledge based systems; Software;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939122