On graph modelling, node ranking and visualisation

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

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)188-210
Number of pages23
JournalInternational Journal of Intelligent Systems Technologies and Applications
Volume3
Issue number3-4
Publication statusPublished - 2007
Externally publishedYes

    Fingerprint

Keywords

  • graph mining
  • graph visualisation
  • web graph

ASJC Scopus subject areas

  • Computer Science(all)

Cite this