A New Clustering Approach for Symbolic Data and its Validation: Application to the Healthcare Data - Archive ouverte HAL
Communication Dans Un Congrès Année : 2006

A New Clustering Approach for Symbolic Data and its Validation: Application to the Healthcare Data

Résumé

Graph coloring is used to characterize some properties of graphs. A b-coloring of a graph G (using colors 1,2,...,k) is a coloring of the vertices of G such that (i) two neighbors have different colors (proper coloring) and (ii) for each color class there exists a dominating vertex which is adjacent to all other k-1 color classes. In this paper, based on a b-coloring of a graph, we propose a new clustering technique. Additionally, we provide a cluster validation algorithm. This algorithm aims at finding the optimal number of clusters by evaluating the property of color dominating vertex. We adopt this clustering technique for discovering a new typology of hospital stays in the French healthcare system.

Domaines

Autre [cs.OH]
Fichier non déposé

Dates et versions

hal-00188994 , version 1 (19-11-2007)

Identifiants

  • HAL Id : hal-00188994 , version 1

Citer

Haytham Elghazel, Véronique Deslandres, Mohand-Said Hacid, Alain Dussauchoy, Hamamache Kheddouci. A New Clustering Approach for Symbolic Data and its Validation: Application to the Healthcare Data. 16th International Symposium on Methodologies for Intelligent Systems, Sep 2006, Bari, Italy. pp.473-482. ⟨hal-00188994⟩
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