43 - Visual Data-Mining Techniques

Abstract

Exploring and analyzing the vast volumes of data has become increasingly difficult. Information visualization and visual data mining can help deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data-mining process. There are a large number of information visualization techniques that were developed in the early 2000s to support the exploration of large datasets. This chapter provides an overview of information visualization and visual data-mining techniques and illustrates them using a few examples. The techniques can be classified based on three criteria: the data to be visualized, the visualization technique, and the interaction technique used. The data type to be visualized may be 1D data, 2D data, multidimensional data; web documents; or hierarchies and graphs such as telephone calls and web documents, algorithms, and software. The visualization technique used may be classified as standard 2D/3D displays—bar charts and x-y plots—geometrically transformed displays—such as hyperbolic plane and parallel coordinates.