A New Clustering Approach for Symbolic Data: Algorithms and Application to Healthcare Data

Abstract : 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.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01586679
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Submitted on : Wednesday, September 13, 2017 - 10:15:13 AM
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  • HAL Id : hal-01586679, version 1

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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⟩

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