An improved algorithm for segregating large geospatial data

Kara E. Scott, Tonny J. Oyana

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

1 Citation (Scopus)

Abstract

This study investigates an improved k-means clustering algorithm for segregating large geospatial data. Although the conventional k-means method is sufficient for datasets with minimal data, it does not perform well and, therefore yields poor accuracy for high-volume datasets. Clustering methods are one of the most important components in data classification, visualization, and mining highvolume datasets. The primary aim of this study is to explore two individual methods that were originally designed to increase the overall performance of k-means clustering: Mashor's updating method and the Davies-Bouldin validity index.

Original languageEnglish (US)
Title of host publicationProceedings 2006 - The 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006
Pages177-185
Number of pages9
StatePublished - 2006
Externally publishedYes
Event9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006 - Visegrad, Hungary
Duration: Apr 20 2006Apr 22 2006

Other

Other9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006
CountryHungary
CityVisegrad
Period4/20/064/22/06

Fingerprint

Clustering algorithms
Visualization
visualization
method
performance

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

Cite this

Scott, K. E., & Oyana, T. J. (2006). An improved algorithm for segregating large geospatial data. In Proceedings 2006 - The 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006 (pp. 177-185)

An improved algorithm for segregating large geospatial data. / Scott, Kara E.; Oyana, Tonny J.

Proceedings 2006 - The 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006. 2006. p. 177-185.

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

Scott, KE & Oyana, TJ 2006, An improved algorithm for segregating large geospatial data. in Proceedings 2006 - The 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006. pp. 177-185, 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006, Visegrad, Hungary, 4/20/06.
Scott KE, Oyana TJ. An improved algorithm for segregating large geospatial data. In Proceedings 2006 - The 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006. 2006. p. 177-185
Scott, Kara E. ; Oyana, Tonny J. / An improved algorithm for segregating large geospatial data. Proceedings 2006 - The 9th AGILE International Conference on Geographic Information Science: "Shaping the Future of Geographic Information Science in Europe", AGILE 2006. 2006. pp. 177-185
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