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Subgraph Isomorphism Detection Using a Code Based Representation.

Iván Olmos, Jesús A. González, Mauricio Osorio

Open publisher page 11 citations

Abstract

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 widthdepth 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.

About this research paper

What this paper is about

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 widthdepth 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.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

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 widthdepth 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.

Key concepts: Subgraph isomorphism problem, Induced subgraph isomorphism problem, Graph isomorphism, Computer science, Isomorphism (crystallography), Representation (politics), Scalability, Theoretical computer science

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