3D Matrix-Based Visualization System of Association Rules

Abstract

With the growing number of association rules, it becomes more and more difficult for users to explore interesting rules due to its nature complexity. Studies base on human perception and intuition show that graphical representation could be a better illustration of how to handle data by using the capabilities of the human visual system to seek information. The 3D matrixbased approach visualization system of association rules called 3DMVS was implemented in present study. The main visual representation employed the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed to generate new rules to reduce the dimension of the association rules, which will help users to find more important items in the new rule. Additionally, several interactions such as sorting, filtering, zoom and rotation, facilitate decision makers to explore the rules they are interested in various aspects. Finally, various evaluation techniques have been employed to assess the system from a logical reasoning point of view.