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LABORATOIRE
INFORMATIQUE, SIGNAUX ET SYSTÈMES DE SOPHIA ANTIPOLIS UMR 6070
HASARD: M INING S EQUENTIAL A SSOCIATION RULES FOR ATHEROSCLEROSIS R ISK FACTOR A NALYSIS Laurent Brisson, Nicolas Pasquier, Martine Collard, Céline Hebert Projet EX E CO Rapport de recherche ISRN I3S/RR–2004-26–FR Octobre 2004
L ABORATOIRE I3S: Les Algorithmes / Euclide B – 2000 route des Lucioles – B.P. 121 – 06903 Sophia-Antipolis Cedex, France – Tél. (33) 492 942 701 – Télécopie : (33) 492 942 898 http://www.i3s.unice.fr/I3S/FR/
R ÉSUMÉ :
M OTS CLÉS : fouille de données, données médicales, motifs séquentiels
A BSTRACT: We present the HASARD method that is an hybrid approach for extracting adaptative temporal association rules. This method extracts assocation rules between events ccuring in subsequent time-intervals using closed itemsets xtraction and evolutionary techniques. An important feature is its capacity to consider different time-intervals depending on the analysed attribute. This method was applied for the analysis of long term medical observations of atherosclerosis risk factors for cardio-vascular diseases prevention. Experimental results show that it is well-suited for extracting knowledge from temporal data where interesting patterns have different observation period length.
K EY WORDS : data mining, medical data, sequential patterns