Internet browsing: visualizing category map by fisheye and fractal views

Abstract

A category map developed based on Kohonen's self-organizing map has been proven to be a promising browsing tool for solving the information overload problem of the World Wide Web. The SOM algorithm automatically compresses and transforms a complex information space into a two-dimensional graphical representation. Such graphical representation provides a user-friendly interface for users to explore the automatically generated mental model. However, as the amount of information increases, the size of the category map is expected to increase accordingly in order to accommodate the important concepts in the information space, which increases the visual load of the category map. In this paper, we propose the fisheye views and fractal views to support the visualization of category map. Fisheye views are developed based on the distortion approach while fractal views are developed based on the information reduction approach. We have developed a prototype system and conducted a user evaluation to investigate the performance of fisheye views and fractal views. The results show that both fisheye views and fractal views significantly increase the effectiveness of visualizing the category map. In addition, fractal views are significantly better than fisheye views.