DocumentCode
3630023
Title
Comparison of Two Document Clustering Techniques which use Neural Networks
Author
I. Mokris;L. Skovajsova
Author_Institution
Slovak Academy of Sciences, Bratislava, Slovakia, mokris@valm.sk
fYear
2008
Firstpage
75
Lastpage
78
Abstract
This paper presents text document space dimension reduction in text document retrieval by two different neural networks and their comparison. First neural network is Hebbian-type neural network, and second neural network is autoassociative neural network which uses backpropagation learning rule. Both neural networks reduce document space to two dimensions so each document is represented as a point in the reduced document space. Moreover, the clusters are formed in reduced document space. Both neural networks give promising results.
Keywords
"Neural networks","Matrix decomposition","Information retrieval","Principal component analysis","Eigenvalues and eigenfunctions","Singular value decomposition","Internet","Computer networks","Backpropagation","Functional analysis"
Publisher
ieee
Conference_Titel
Computational Cybernetics, 2008. ICCC 2008. IEEE International Conference on
Print_ISBN
978-1-4244-2874-8
Type
conf
DOI
10.1109/ICCCYB.2008.4721382
Filename
4721382
Link To Document