WDM: A New Efficient Visualization Method of Classifying Web Documents Based on SOM

Author

Bai, Xi ; Sun, Jigui ; Luo, Hong

Author_Institution

Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun

Volume

1

fYear

2006

fDate

Nov. 2006

Firstpage

809

Lastpage

814

Abstract

We propose a new visualization method WDM to classify documents by adding in the position-factors of words such as the title-factor and the first-sentence-factor based on a SOM neural network. We also discuss the selection of the function which is used to calculate the belong-to-probability in neurons´ reflecting process. The experimental results indicate that WDM makes the boundaries of different documents greatly more clear, and thus it can produce more accurate and intuitive classification compared to the visualization methods which do not have position-factors considered

Keywords

Web sites; data visualisation; document handling; pattern classification; self-organising feature maps; SOM neural network; Web document classification; efficient visualization method; Computer networks; Computer science; Educational institutions; Educational technology; Laboratories; Neural networks; Neurons; Sun; Visualization; Wavelength division multiplexing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2006 International Conference on

Conference_Location

Guangzhou

Print_ISBN

1-4244-0605-6

Electronic_ISBN

1-4244-0605-6

Type

conf

DOI

10.1109/ICCIAS.2006.294248

Filename

4072201