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Conference papers
HASAR : mining sequential association rules for atherosclerosis risk factor analysis
Abstract : We present the HASAR method that is an hybrid approach for ex- tracting adaptive sequential association rules. This method extracts association rules between events occurring in subsequent time-intervals using closed itemsets extraction and evolutionary techniques. An important feature is its capacity to consider different time-intervals depending on the attributes semantic. We applied this method 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.
Keywords :
Data mining
Association rules
https://hal.archives-ouvertes.fr/hal-02341338
Contributor : Bibliothèque Télécom Bretagne <>
Submitted on : Thursday, October 31, 2019 - 12:37:36 PM
Last modification on : Monday, October 12, 2020 - 10:30:31 AM
Long-term archiving on: : Saturday, February 1, 2020 - 5:27:19 PM
Contributor : Bibliothèque Télécom Bretagne <>
Submitted on : Thursday, October 31, 2019 - 12:37:36 PM
Last modification on : Monday, October 12, 2020 - 10:30:31 AM
Long-term archiving on: : Saturday, February 1, 2020 - 5:27:19 PM
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brisson-hasar.pdf
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