DocumentCode :
389677
Title :
A study of dynamic knowledge representation based on neural networks
Author :
Pan, Hao ; Zhong, Luo ; Yuan, Jing-ling
Author_Institution :
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., China
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
126
Abstract :
The competitive learning technique is a well-known algorithm used in neural networks, which classifies the input vectors, so that the vectors (samples) belonging to the same class have similar characteristics. Dynamic competitive learning is an unsupervised learning technique, which consists of two additional parts related to conventional competitive learning: a method of generation of new units within a cluster; and a method of generating new clusters. The model is capable for the high-level storage of complex data structures, whose classification include exception handling.
Keywords :
data structures; exception handling; knowledge representation; neural nets; pattern clustering; unsupervised learning; cluster knowledge representation; data structures; dynamic competitive learning; exception handling; heuristic method; neural networks; unsupervised learning; Character generation; Clustering algorithms; Computer science; Data structures; Electronic mail; Equations; Image processing; Multi-layer neural network; Neural networks; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
Type :
conf
DOI :
10.1109/ICMLC.2002.1176723
Filename :
1176723
Link To Document :
بازگشت