Subgraph Isomorphism Detection Using a Code Based Representation

Ivan Olmos and Jesus A. Gonzalez, Instituto Nacional de Astrofísica, óptica, y Electrónica; and Mauricio Osorio, Universidad de las Américas Puebla

Subgraph Isomorphism Detection is an important problem for several computer science subfields, where a graph-based representation is used. In this research we present a new approach to find a Subgraph Isomorphism (SI) using a list code based representation without candidate generation. We implement a step by step expansion model with a width-depth search. Our experiments show a promising method to be used with scalable graph matching tools to find interesting patterns in Machine Learning and Data Mining applications.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.