%0 Journal Article
	%A Amdouni Hamida and  Gammoudi Mohamed Mohsen
	%D 2015
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 104, 2015
	%T Semi-Automatic Method to Assist Expert for Association Rules Validation
	%U https://publications.waset.org/pdf/10002201
	%V 104
	%X In order to help the expert to validate association rules
extracted from data, some quality measures are proposed in the
literature. We distinguish two categories: objective and subjective
measures. The first one depends on a fixed threshold and on data
quality from which the rules are extracted. The second one consists
on providing to the expert some tools in the objective to explore and
visualize rules during the evaluation step. However, the number of
extracted rules to validate remains high. Thus, the manually mining
rules task is very hard. To solve this problem, we propose, in this
paper, a semi-automatic method to assist the expert during the
association rule's validation. Our method uses rule-based
classification as follow: (i) We transform association rules into
classification rules (classifiers), (ii) We use the generated classifiers
for data classification. (iii) We visualize association rules with their
quality classification to give an idea to the expert and to assist him
during validation process.
	%P 1919 - 1927