Title :
System for document clustering from mixed sources based on Fuzzy ART neural network
Author :
Rojcek, Michal ; Mokris, Igor
Author_Institution :
Dept. of Inf., Catholic Univ. in Ruzomberok, Ruzomberok, Slovakia
Abstract :
The article presents a model for text document clustering based on Fuzzy ART neural network with two separate network segments. The first segment (Internet) enables clustering for the classification of documents into new categories, and the second segment (intranet) enables the modified Fuzzy ART algorithm to assign documents into existing categories. The article observe behavior of the model based on Fuzzy ART network, into which entering the different strategies in the different segments of synthetic text documents.
Keywords :
ART neural nets; Internet; fuzzy neural nets; intranets; pattern classification; pattern clustering; text analysis; Internet; adaptive resonance theory; document classification; fuzzy ART neural network; intranet; network segments; synthetic text documents; text document clustering; Clustering algorithms; Information retrieval; Internet; Neural networks; Subspace constraints; Testing; Vectors;
Conference_Titel :
System Science and Engineering (ICSSE), 2013 International Conference on
Conference_Location :
Budapest
Print_ISBN :
978-1-4799-0007-7
DOI :
10.1109/ICSSE.2013.6614670
