Exploring the data using Extended Association Rule Network

• Autor(a) principal: Padua, Renan de
• Data de Publicação: 2018
• Outros Autores: Calcada, Dario Brito, Carvalho, Veronica Oliveira de [UNESP], Rezende, Solange Oliveira, IEEE
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/BRACIS.2018.00064; http://hdl.handle.net/11449/186619
• topic: Association Rules; Association Rules Network; Hypothesis building; Data Analysis and Market Basket Analysis

In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building.