A User Assistant for the Selection and Parameterization of the Visualizations in Visual Data Mining
Résumé
We deal in this paper with the problem of automating the process of choosing an appropriate visualization and its parameters in the context of visual data mining (VDM). To solve this problem, we develop a user assistant that performs 2 steps: the system starts by suggesting to users different mappings between their data and possible visualizations. This is performed with a simple but generic heuristic that can be applied to any visualization. Then, the user selects a visualization among those proposed by our assistant, and he may further improve the parameters set that defines the mapping between the visual attributes and the data attributes. For this purpose, we use an interactive genetic algorithm (IGA), which allows users to visually evaluate and adjust the mappings. We present a user evaluation that confirms the interest of our system in two tasks.