doi: 10.7763/IJCTE.2009.V1.99
Classification of Documents Using Kohonen’s Self-Organizing Map
B. H. ChandraShekar1
,
G. Shoba2
- 1Department of Master of Computer Applications, R. V. College of Engineering, Mysore Raod, Bangalore 560059, India.
- 2College of Engineering, Mysore Road, Bangalaore 560059, India.
Abstract
Innovative methods that are user friendly and efficient are needed for retrieval of textual information available on the World Wide Web. The self-organizing map (SOM) is one of the most widely used neural network algorithms. SOM can be used to identify clusters of documents with similar context and content. In this paper, we explore and visualize the Self Organizing Map and discuss how to classify text documents. The paper also portrays the capabilities of SOM in text classification. We also discuss about experiments done using 20 news group dataset.
Keywords
- Self-organizing map
- stop words
- term-document
- neurons
How to Cite
B. H. ChandraShekar and G. Shoba, "Classification of Documents Using Kohonen’s Self-Organizing Map," International Journal of Computer Theory and Engineering, vol. 1, no. 5, pp. 610-613, 2009. https://doi.org/10.7763/IJCTE.2009.V1.99
Copyright & License
Copyright © 2009 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).