Improving the web text content by extracting significant pages into a Web Site

Sebastián A. Ríos, Juan D. Velásquez, Eduardo S. Vera, Hiroshi Yasuda, Terumasa Aoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Web Systems have reached a very important role in today's business world. Every day organizations fight to keep their present clients and to gain new ones. In order to accomplish this goal it is very important to make precise changes in the web site content. However, the development of these improvements is a complex and specialized task because of the nature of the web data itself. We propose a novel approach to successfully make changes to improve the web site content using text mining. We use a Self Organizing Feature Map (SOFM)to find the most relevant text content, and then we propose a reverse clustering analysis in order to extract the most significant pages of the whole web site. The effectiveness of this method was experimentally tested in a real web site.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Intelligent Systems Design and Applications, ISDA '05
Pages32-36
Number of pages5
DOIs
Publication statusPublished - 2005 Dec 1
Event5th International Conference on Intelligent Systems Design and Applications, ISDA '05 - Wroclaw, Poland
Duration: 2005 Sep 82005 Sep 10

Publication series

NameProceedings - 5th International Conference on Intelligent Systems Design and Applications 2005, ISDA '05
Volume2005

Other

Other5th International Conference on Intelligent Systems Design and Applications, ISDA '05
CountryPoland
CityWroclaw
Period05/9/805/9/10

ASJC Scopus subject areas

  • Engineering(all)

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