DocumentCode :
3631316
Title :
Document space dimension reduction by nonlinear Hebbian neural network
Author :
Lenka Skovajsova;Igor Mokris
fYear :
2009
Firstpage :
89
Lastpage :
91
Abstract :
This paper deals with information retrieval of text documents, and their clustering into some other feature space. The aim of this paper is to reduce the dimension of the document space by the nonlinear Hebbian neural network. As can be seen from the results, not only dimension reduction of document space is made, but also clustering of these documents into clusters. We used here the nonlinear Hebbian neural network, which is feed-forward neural network with unsupervised learning.
Keywords :
"Neural networks","Information retrieval","Feedforward neural networks","Matrix decomposition","Principal component analysis","Indexing","Strontium","Sparse matrices","Feedforward systems","Unsupervised learning"
Publisher :
ieee
Conference_Titel :
Applied Machine Intelligence and Informatics, 2009. SAMI 2009. 7th International Symposium on
Print_ISBN :
978-1-4244-3801-3
Type :
conf
DOI :
10.1109/SAMI.2009.4956615
Filename :
4956615
Link To Document :
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