Mining common patterns on graphs

Authors:
Ivan Olmos;Jesus A. Gonzalez;Mauricio Osorio
Affiliations:
Instituto Nacional de Astrofísica, Óptica y Electrónica, Sta. Maria Tonantzintla, Puebla, México;Instituto Nacional de Astrofísica, Óptica y Electrónica, Sta. Maria Tonantzintla, Puebla, México;Universidad de las Américas Puebla, Sta. Catarina Mártir, Puebla, México
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

Finding common patterns is an important problem for several computer science subfields such as Machine Learning (ML) and Data Mining (DM). When we use graph-based representations, we need the Subgraph Isomorphism (SI) operation for finding common patterns. In this research we present a new approach to find a SI using a list code based representation without candidate generation. We implement a step by step expansion model with a width-depth search. The proposed approach is suitable to work with labeled and unlabeled graphs, with directed and undirected edges. Our experiments show a promising method to be used with scalable graph matching.