July 4, 2007 to July 6, 2007
Olivier Couturier , Universit? d?Artois, IUT de Lens, France
Tarek Hamrouni , Campus Universitaire, Tunis, Tunisie
Sadok Ben Yahia , Campus Universitaire, Tunis, Tunisie
Engelbert Mephu Nguifo , Universit? d?Artois, IUT de Lens, France
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IV.2007.16
Providing efficient and easy-to-use graphical tools to users is a promising challenge of data mining (DM). These tools must be able to generate explicit knowledge and to restitute it. Visualization techniques have shown to be an efficient solution to achieve such goal. Even though considered as a key step in the mining process, the visualization step of association rules received much less attention than that paid to the extraction one. Nevertheless, some graphical tools have been developed to extract and visualize association rules. In those tools, various approaches are proposed to filter the huge number of association rules before the visualization step. However both DM steps (association rule extraction and visualization) are treated separately in a one way process. Our approach differs, and uses meta-knowledge to guide the user during the mining process. Standing at the crossroads of DM and Human-Computer Interaction (HCI), we present an integrated framework covering both steps of the DM process. Furthermore, our approach can easily integrate previous techniques of association rule visualization.
Olivier Couturier, Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu Nguifo, "A scalable association rule visualization towards displaying large amounts of knowledge", IV, 2007, 2013 17th International Conference on Information Visualisation, 2013 17th International Conference on Information Visualisation 2007, pp. 657-663, doi:10.1109/IV.2007.16