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

A New Clustering Approach for Symbolic Data: Algorithms and Application to 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, we build on b-coloring of a graph to propose a new clustering technique. 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.
Fichier non déposé

Dates et versions

hal-01586679 , version 1 (13-09-2017)

Identifiants

  • HAL Id : hal-01586679 , version 1

Citer

Haytham Elghazel, Mohand-Said Hacid, Hamamache Khedouci, Alain Dussauchoy. A New Clustering Approach for Symbolic Data: Algorithms and Application to Healthcare Data. 22èmes Journées Bases de Données Avancées, BDA 2006, Oct 2006, Lille, France. ⟨hal-01586679⟩
104 Consultations
0 Téléchargements

Partager

More