Title: On graph modelling, node ranking and visualisation

Authors: Xiaodi Huang, Dianhui Wang, Kazuo Misue, Jiro Tanaka, A.S.M. Sajeev

Addresses: Department of Mathematics, Statistics and Computer Science, University of New England, Australia. ' Department of Computer Science and Computer Engineering, La Trobe University, Australia. ' Department of Computer Science, Graduate School of Systems and Information Engineering, University of Tsukuba, Japan. ' Department of Computer Science, Graduate School of Systems and Information Engineering, University of Tsukuba, Japan. ' Department of Mathematics, Statistics and Computer Science, The University of New England, Australia

Abstract: Graphs traditionally have many applications in various areas of computer science. Research in graph-based data mining has recently gained a high level of attraction due to its broad range of applications. Examples include XML documents, web logs, web searches and molecular biology. Most of the approaches used in these applications focus on deriving interesting, frequent patterns from given datasets. Two fundamental questions are, however, ignored; that is, how to derive a graph from a set of objects and how to order nodes according to their relations with others in the graph. In this paper, we provide approaches to building a graph from a given set of objects accompanied by their feature vectors, as well as to ranking nodes in the graph. The basic idea of our ranking approach is to quantify the important role of a node as the degree to which it has direct and indirect relationships with other nodes in a graph. A method for visualising graphs with ranking nodes is also presented. The visual examples and applications are provided to demonstrate the effectiveness of our approaches.

Keywords: graph mining; graph visualisation; web graphs; node ranking; feature vectors; graph modelling; pattern recognition.

DOI: 10.1504/IJISTA.2007.014259

International Journal of Intelligent Systems Technologies and Applications, 2007 Vol.3 No.3/4, pp.188 - 210

Published online: 28 Jun 2007 *

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