GeoSOM suite: A tool for spatial clustering

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

4 Citations (Scopus)

Abstract

The large amount of spatial data available today demands the use of data mining tools for its analysis. One of the most used data mining techniques is clustering. Several methods for spatial clustering exist, but many consider space as just another variable. We present in this paper a tool particularly suited for spatial clustering: the GeoSOM suite. This tool implements the GeoSOM algorithm, which is based on Self-Organizing Maps. This paper describes this tool, and shows that it is adequate for exploring spatial data.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2009 - International Conference, Proceedings
Pages453-466
Number of pages14
EditionPART 1
DOIs
Publication statusPublished - 9 Nov 2009
EventInternational Conference on Computational Science and Its Applications, ICCSA 2009 - Seoul, Korea, Republic of
Duration: 29 Jun 20092 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5592 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Computational Science and Its Applications, ICCSA 2009
CountryKorea, Republic of
CitySeoul
Period29/06/092/07/09

Keywords

  • Exploratory spatial data analysis
  • Self-organizing maps
  • Spatial clustering

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