Solving Graph Homomorphism and Subgraph Isomorphism Problems Faster Through Clique Neighbourhood Constraints

Kraiczy, S. and McCreesh, C. (2021) Solving Graph Homomorphism and Subgraph Isomorphism Problems Faster Through Clique Neighbourhood Constraints. In: Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), Montréal, Canada, 19-27 Aug 2021, pp. 1396-1402. ISBN 9780999241196 (doi: 10.24963/ijcai.2021/193)

Abstract

Graph homomorphism problems involve finding adjacency-preserving mappings between two given graphs. Although theoretically hard, these problems can often be solved in practice using constraint programming algorithms. We show how techniques from the state-of-the-art in subgraph isomorphism solving can be applied to broader graph homomorphism problems, and introduce a new form of filtering based upon clique-finding. We demonstrate empirically that this filtering is effective for the locally injective graph homomorphism and subgraph isomorphism problems, and gives the first practical constraint programming approach to finding general graph homomorphisms.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Kraiczy, Ms Sonja and Mccreesh, Dr Ciaran
• Authors: Kraiczy, S., and McCreesh, C.
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 9780999241196
• Copyright Holders: Copyright © 2021 International Joint Conferences on Artificial Intelligence
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
300525		Modelling and Optimisation with Graphs	Patrick Prosser	Engineering and Physical Sciences Research Council (EPSRC)	EP/P026842/1	Computing Science