Authors:
Magaly Lika Fujimoto
1
;
Veronica Oliveira de Carvalho
2
and
Solange Oliveira Rezende
1
Affiliations:
1
São Paulo University, Brazil
;
2
Oeste Paulista University, Brazil
Keyword(s):
Generalized association rules, Objective measures, Subjective measures, Visualization, Knowledge evaluation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Considering the user view, many problems can be found during the post-processing of association rules, since a large number of patterns can be obtained, which complicates the comprehension and identification of interesting knowledge. Thereby, this paper proposes an approach to improve the knowledge comprehensibility and to facilitate the identification of interesting generalized association rules during evaluation. This aid is realized combining objective and subjective measures with information visualization techniques, implemented on a system called RulEE-GARVis .