Web site improvements based on representative pages identification

Sebastían A. Ríos, Juan D. Velásquez, Hiroshi Yasuda, Terumasa Aoki

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

7 Citations (Scopus)

Abstract

Many researchers have successfully shown that web content mining technics and web usage mining techniques can help to find out important patterns on the content and browsing behavior in a site. However, still it is an open problem how to reach a good interpretation of the cluster results after the mining process. We propose a technique called Reverse Clustering Analysis (RCA) applied to a Self Organizing Feature Map in order to identify the most representative Web Pages of the Site. Then use this information to perform enhancements in the site. Our mining process is based on the combination of WCM and WUM to find out the content that is most interesting for the visitors. We successfully test our proposal in a real web site.

Original languageEnglish
Title of host publicationAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings
Pages1162-1166
Number of pages5
Publication statusPublished - 2005 Dec 1
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 2005 Dec 52005 Dec 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
CountryAustralia
CitySydney
Period05/12/505/12/9

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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