A Visualization Model of Interactive Knowledge Discovery Systems and Its Implementations

Abstract

We briefly introduce an interactive visualization model, RuleViz, for knowledge discovery and data mining, which consists of five components: data preparation and visualization, interactive data reduction, data preprocessing, pattern discovery, and pattern visualization. With this model, the implementation issues are considered and three implementation paradigms, including image-based paradigm, algorithm-embedded paradigm, and interaction-driven paradigm, are discussed. We implement an interactive visualization system, AViz, which discovers 3D numerical association rules from large data sets based on the image-based paradigm. The framework of the AViz system is presented and each component is explored. To discretize numerical attributes, three approaches, including equal-sized, bin-packing-based equal-depth, and interaction-based approaches are proposed, and the algorithm for mining and visualizing numerical association rules is developed. Our experimental result on a census data set is illustrated, which shows that the AViz system is useful and helpful for discovering and visualizing numerical association rules.