Between Subgraph Isomorphism and Maximum Common Subgraph

Hoffmann, R., Mccreesh, C. and Reilly, C. (2017) Between Subgraph Isomorphism and Maximum Common Subgraph. In: Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, CA, USA, 4-10 Feb 2017, pp. 3907-3914.

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When a small pattern graph does not occur inside a larger target graph, we can ask how to find "as much of the pattern as possible" inside the target graph. In general, this is known as the maximum common subgraph problem, which is much more computationally challenging in practice than subgraph isomorphism. We introduce a restricted alternative, where we ask if all but k vertices from the pattern can be found in the target graph. This allows for the development of slightly weakened forms of certain invariants from subgraph isomorphism which are based upon degree and number of paths. We show that when k is small, weakening the invariants still retains much of their effectiveness. We are then able to solve this problem on the standard problem instances used to benchmark subgraph isomorphism algorithms, despite these instances being too large for current maximum common subgraph algorithms to handle. Finally, by iteratively increasing k, we obtain an algorithm which is also competitive for the maximum common subgraph.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Mccreesh, Dr Ciaran and Reilly, Mr Craig and Hoffmann, Dr Ruth
Authors: Hoffmann, R., Mccreesh, C., and Reilly, C.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2017 Association for the Advancement of Artificial Intelligence
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
608951Engineering and Physical Sciences Doctoral Training Grant 2012-16Mary Beth KneafseyEngineering & Physical Sciences Research Council (EPSRC)EP/K503058/1VPO VICE PRINCIPAL RESEARCH & ENTERPRISE