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The BANG-clustering system: Grid-based data analysis

  • Erich Schikuta
  • Martin Erhart
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1280)

Abstract

For the analysis of large images the clustering of the data set is a common technique to identify correlation characteristics of the underlying value space. In this paper a new approach to hierarchical clustering of very large data sets is presented. The BANG-Clustering system presented in this paper is a novel approach to hierarchical data analysis. It is based on the BANG-Clustering method ([Sch96]) and uses a multidimensional grid data structure to organize the value space surrounding the pattern values. The patterns are grouped into blocks and clustered with respect to the blocks by a topological neighbor search algorithm.

Keywords

Cluster Algorithm Cluster Center Neighbor Search Data Block Density Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1997

Authors and Affiliations

  • Erich Schikuta
    • 1
  • Martin Erhart
    • 1
  1. 1.Institute of Applied Computer Science and Information SystemsUniversity of ViennaViennaAustria

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