From Visualization to Association Rules : an automatic approach

Gwenael Bothorel 1, 2 Mathieu Serrurier 2 Christophe Hurter 3
1 DGAC - Direction Générale de l'Aviation Civile
2 IRIT - Institut de recherche en informatique de Toulouse
3 LII - ENAC - Laboratoire d'Informatique Interactive
Abstract : The main goal of Data Mining is the research of relevant information from a huge volume of data. It is generally achieved either by automatic algorithms or by the visual exploration of data. Thanks to algorithms, an exhaustive set of patterns matching specific measures can be found. But the volume of extracted information can be greater than the volume of initial data. Visual Data Mining allows the specialist to focus on a specific area of data that may describe interesting patterns. However, it is often limited by the difficulty to deal with a great number of multi dimensional data. In this paper, we propose to mix an automatic and a manual method, by driving the automatic extraction using a data scatter plot visualization. This visualization affects the number of rules found and their construction. We illustrate our method on two databases. The first describes one month French air traffic and the second stems from 2012 KDD Cup database.
Document type :
Conference papers
Liste complète des métadonnées

Cited literature [9 references]  Display  Hide  Download
https://hal-enac.archives-ouvertes.fr/hal-01078330
Contributor : Laurence Porte <>
Submitted on : Tuesday, December 16, 2014 - 5:57:19 PM
Last modification on : Friday, April 12, 2019 - 4:23:01 PM
Document(s) archivé(s) le : Saturday, April 15, 2017 - 9:35:04 AM

File

057-bothorel.done.pdf
Publisher files allowed on an open archive

Identifiers

Collections

ENAC | UNIV-TLSE2 | UNIV-TLSE3 | LII | DGAC | SMS

Citation

Gwenael Bothorel, Mathieu Serrurier, Christophe Hurter. From Visualization to Association Rules : an automatic approach. SCCG 2013, Spring Conference on Computer Graphics, ACM, May 2013, Smolenice, Slovakia. pp 57-64, ⟨10.1145/2508244.2508252⟩. ⟨hal-01078330⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

355

Files downloads

145