 |
Communication dans un congrès
From Visualization to Association Rules : an automatic approach
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.
Littérature citée [9 références]
https://hal-enac.archives-ouvertes.fr/hal-01078330
Contributeur : Laurence Porte Connectez-vous pour contacter le contributeur
Soumis le : mardi 16 décembre 2014 - 17:57:19
Dernière modification le : mardi 19 octobre 2021 - 14:24:13
Archivage à long terme le : : samedi 15 avril 2017 - 09:35:04
Contributeur : Laurence Porte Connectez-vous pour contacter le contributeur
Soumis le : mardi 16 décembre 2014 - 17:57:19
Dernière modification le : mardi 19 octobre 2021 - 14:24:13
Archivage à long terme le : : samedi 15 avril 2017 - 09:35:04
Fichier
057-bothorel.done.pdf
Fichiers éditeurs autorisés sur une archive ouverte