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
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"
Conference_Titel :
Computational Cybernetics, 2008. ICCC 2008. IEEE International Conference on
Print_ISBN :
978-1-4244-2874-8
DOI :
10.1109/ICCCYB.2008.4721382