Leveraging a web-aware self-organization map tool for clustering and visualization

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

1 Citation (Scopus)

Abstract

The self-organization map (SOM) neural network has been recognized as a successful paradigm for clustering and visualization in a large variety of real-world applications. There exist a number of useful stand-alone SOM tools, however, they cannot be adapted to the new generation web environment. In addition, different user interfaces required for operation and the heterogeneity of platforms where the tools run on prevent them from appeal. In this paper, we propose a web-aware SOM tool which integrates the computationally powerful SOM PAK and the vivid Nenet tools to augment the advantages of each. The proposed SOM tool is capable of delimiting the desired clusters by adopting two level network topology and silhouette coefficients.

Original languageEnglish
Title of host publicationWeb Intelligence
Subtitle of host publicationResearch and Development - 1st Asia-Pacific Conference, WI 2001, Proceedings
EditorsJiming Liu, Ning Zhong, Yiju Yao, Setsuo Ohsuga
PublisherSpringer Verlag
Pages579-583
Number of pages5
ISBN (Print)3540427309, 9783540427308
Publication statusPublished - 2001 Jan 1
Event1st Asia-Pacific Conference on Web Intelligence, WI 2001 - Maebashi City, Japan
Duration: 2001 Oct 232001 Oct 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2198
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st Asia-Pacific Conference on Web Intelligence, WI 2001
CountryJapan
CityMaebashi City
Period01-10-2301-10-26

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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