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A Graph-Based Clustering Method and Its Applications

  • Pasquale Foggia
  • Gennaro Percannella
  • Carlo Sansone
  • Mario Vento
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4729)

Abstract

In this paper we present a graph-based clustering method particularly suited for dealing with data that do not come from a Gaussian or a spherical distribution. It can be used for detecting clusters of any size and shape, without the need of specifying neither the actual number of clusters nor other parameters.

The method has been tested on data coming from two different computer vision applications. A comparison with other three state-of-the-art algorithms was also provided, demonstrating the effectiveness of the proposed approach.

Keywords

Cluster Algorithm Minimum Span Tree News Video Cluster Detection Mammographic Image 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Pasquale Foggia
    • 1
  • Gennaro Percannella
    • 2
  • Carlo Sansone
    • 1
  • Mario Vento
    • 2
  1. 1.Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II, Via Claudio, 21 I-80125 NapoliItaly
  2. 2.Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica, Università di Salerno, via P.te Don Melillo, I-84084 Fisciano (SA)Italy

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