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VISUALIZATION OF A SYNTHETIC REPRESENTATION OF ASSOCIATION RULES TO ASSIST EXPERT VALIDATION
BibTeX
@MISC{Hamida_visualizationof,
author = {Amdouni Hamida and Gammoudi Mohamed Mohsen},
title = {VISUALIZATION OF A SYNTHETIC REPRESENTATION OF ASSOCIATION RULES TO ASSIST EXPERT VALIDATION},
year = {}
}
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Abstract
In order to help the expert to validate association rules, 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 structure from which the rules are extracted. The second one has two subcategories: The first one consists on providing to the expert a tool for rule interactive exploration. In fact, they present these rules in textual form. The second subcategory includes the use of visualization systems to facilitate the task of rules mining. However, this last subcategory assumes that experts have statistical knowledge to interpret and validate association rules. Furthermore, the statistical methods have a lack of semantic representation and could not help the experts during the process of validation. To solve this problem, we propose in this paper a method which visualizes to the experts a synthetic representation of association rules as a formal conceptual graph (FCG). FCG represents his area of interest and allows him to realize the task of rules mining easily due to its semantic richness.
Keyphrases
association rule data structure semantic richness visualization system textual form formal conceptual graph semantic representation statistical knowledge synthetic representation subjective measure statistical method second subcategory rule interactive exploration quality measure last subcategory
