Solving graph isomorphism using parameterized matching

Juan Mendivelso, Sunghwan Kim, Sameh Elnikety, Yuxiong He, Seung Won Hwang, Yoan Pinzón

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)


We propose a new approach to solve graph isomorphism using parameterized matching. To find isomorphism between two graphs, one graph is linearized, i.e. , represented as a graph walk that covers all nodes and edges such that each element is represented by a parameter. Next, we match the graph linearization on the second graph, searching for a bijective function that maps each element of the first graph to an element of the second graph. We develop an efficient linearization algorithm that generates short linearization with an approximation guarantee, and develop a graph matching algorithm. We evaluate our approach experimentally on graphs of different types and sizes, and compare to the performance of VF2, which is a prominent algorithm for graph isomorphism. Our empirical measurements show that graph linearization finds a matching graph faster than VF2 in many cases because of better pruning of the search space.

Original languageEnglish
Title of host publicationString Processing and Information Retrieval - 20th International Symposium, SPIRE 2013, Proceedings
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783319024318
Publication statusPublished - 2013
Event20th International Symposium on String Processing and Information Retrieval, SPIRE 2013 - Jerusalem, Israel
Duration: 2013 Oct 72013 Oct 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8214 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other20th International Symposium on String Processing and Information Retrieval, SPIRE 2013

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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