Fractal Analysis of Knowledge Organization in Digital Library

Abstract

Visualization of the large-scale collections of information became one of the essential purpose in data analysis. The new methods of visualization are increasingly applied as a significant component in scientific research. Particularly qualitative nature of Infoviz studies (Information visualization) can be combined with quantitative character of digital libraries volumes. This paper describes and demonstrates the case of hierarchical structure visualization i.e. visual representation of both classification adopted by ACM (Association for Computing Machinery ) digital library and classification universe. Given maps were processed by nonlinear graphical filters. Finally fractal dimension (FD) and derived techniques have used to analyze the patterns of clusters on the visualization maps. Quantification of output graphical representation by means of fractals makes possible to adjust visualization parameters as well as evaluate initial classification scheme and its dynamical characteristics.