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