International Conference on Belief Functions

BELIEF 2014: Belief Functions: Theory and Applications pp 68-76 | Cite as

Belief Hierarchical Clustering

  • Wiem Maalel
  • Kuang Zhou
  • Arnaud Martin
  • Zied Elouedi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8764)

Abstract

In the data mining field many clustering methods have been proposed, yet standard versions do not take into account uncertain databases. This paper deals with a new approach to cluster uncertain data by using a hierarchical clustering defined within the belief function framework. The main objective of the belief hierarchical clustering is to allow an object to belong to one or several clusters. To each belonging, a degree of belief is associated, and clusters are combined based on the pignistic properties. Experiments with real uncertain data show that our proposed method can be considered as a propitious tool.

Keywords

Clustering Hierarchical clustering Belief function Belief clustering 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Wiem Maalel
    • 1
    • 2
  • Kuang Zhou
    • 1
    • 2
  • Arnaud Martin
    • 1
    • 2
  • Zied Elouedi
    • 1
    • 2
  1. 1.LARODEC, ISG.Le BardoTunisia
  2. 2.IRISA,Université de Rennes 1. IUT de Lannion.Lannion cedexFrance

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