PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Graph Characteristics from the Ihara Zeta Function
Peng Ren, Richard Wilson and Edwin Hancock
In: SSPR/SPR 2008, Dec 4-6, 2008, Orlando, USA.

Abstract

This paper shows how to extract permutation invariant graph characteristics from the Ihara zeta function. In a previous paper, we have shown that the Ihara zeta function leads to a polynomial characterization of graph structure, and we have shown empirically that the coefficients of the polynomial can be used as to cluster graphs. The aim in this paper is to take this study further by showing how to select the most significant coefficients and how these can be used to gauge graph similarity. Experiments on real-world datasets reveal that the selected coefficients give results that are significantly better than those obtained with the Laplacian spectrum.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:6876
Deposited By:Edwin Hancock
Deposited On:08 April 2010