Building and Assessing a Constrained Clustering Hierarchical Algorithm

  • Eduardo R. Concepción Morales
  • Yosu Yurramendi Mendizabal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)


Unsupervised classification or clustering has been used in many disciplines and contexts. Traditional methodologies are mostly based on the minimization of the distance between data and the cluster means without considering any other possible relationship present in data, e.g., spatial interactions. A constrained hierarchical agglomerative algorithm with an aggregation index is introduced which uses neighbouring relations present in the data. Experiments show the behaviour of the proposed constrained algorithm in different situations.


constrained clustering methods agglomerative hierarchical classification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Eduardo R. Concepción Morales
    • 1
  • Yosu Yurramendi Mendizabal
    • 2
  1. 1.Faculty of InformaticsUniversity of CienfuegosCuatro CaminosCuba
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of the Basque Country/EHUDonostia-San SebastianSpain

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