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The VF3-Light Subgraph Isomorphism Algorithm: When Doing Less Is More Effective

  • Vincenzo Carletti
  • Pasquale Foggia
  • Antonio Greco
  • Alessia Saggese
  • Mario Vento
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11004)

Abstract

We have recently intoduced VF3, a general-purpose subgraph isomorphism algorithm that has demonstrated to be very effective on several datasets, especially on very large and very dense graphs.

In this paper we show that on some classes of graphs, the whole power of VF3 may become overkill; indeed, by removing some of the heuristics used in it, and as a consequence also some of the data structures that are required by them, we obtain an algorithm that is actually faster.

In order to provide a characterization of this modified algorithm, called VF3-Light, we have performed an evaluation using several kinds of graphs; besides comparing VF3-Light with VF3, we have also compared it to RI, a fast recent algorithm that is based on a similar approach.

References

  1. 1.
    Conte, D., Foggia, P., Sansone, C., Vento, M.: Thirty years of graph matching in pattern recognition. Int. J. Pattern Recogn. Artif. Intell. 18(3), 265–298 (2004)CrossRefGoogle Scholar
  2. 2.
    Foggia, P., Percannella, G., Vento, M.: Graph matching and learning in pattern recognition on the last ten years. Int. J. Pattern Recogn. Artif. Intell. 28(1), 1450001 (2014)CrossRefGoogle Scholar
  3. 3.
    Vento, M.: A long trip in the charming world of graphs for pattern recognition. Pattern Recogn. 48, 1–11 (2014)CrossRefGoogle Scholar
  4. 4.
    Ullmann, J.R.: An algorithm for subgraph isomorphism. J. Assoc. Comput. Mach. 23, 31–42 (1976)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Cordella, L., Foggia, P., Sansone, C., Vento, M.: A (sub)graph isomorphism algorithm for matching large graphs. IEEE Trans. Pattern Anal. Mach. Intell. 26, 1367–1372 (2004)CrossRefGoogle Scholar
  6. 6.
    Almasri, I., Gao, X., Fedoroff, N.: Quick mining of isomorphic exact large patterns from large graphs. In: IEEE International Conference on Data Mining Workshop, pp. 517–524, December 2014Google Scholar
  7. 7.
    Bonnici, V., Giugno, R.: On the variable ordering in subgraph isomorphism algorithms. IEEE/ACM Trans. Comput. Biol. Bioinform. 14(1), 193–203 (2017)CrossRefGoogle Scholar
  8. 8.
    Carletti, V., Foggia, P., Saggese, A., Vento, M.: Challenging the time complexity of exact subgraph isomorphism for huge and dense graphs with VF3. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 804–818 (2018)CrossRefGoogle Scholar
  9. 9.
    Carletti, V., Foggia, P., Saggese, A., Vento, M.: Introducing VF3: a new algorithm for subgraph isomorphism. In: Foggia, P., Liu, C.L., Vento, M. (eds.) GbRPR 2017, pp. 128–139. Springer International Publishing, Cham (2017).  https://doi.org/10.1007/978-3-319-58961-9-12CrossRefGoogle Scholar
  10. 10.
    MIVIA Lab: MIVIA dataset and MIVIA large dense graphs dataset (2017). http://mivia.unisa.it/
  11. 11.
    Bonnici, V., Giugno, R., Pulvirenti, A., Shasha, D., Ferro, A.: A subgraph isomorphism algorithm and its application to biochemical data. BMC Bioinform. 14, S13 (2013)CrossRefGoogle Scholar
  12. 12.
    Carletti, V., Foggia, P., Vento, M., Jiang, X.: Report on the first contest on graph matching algorithms for pattern search in biological databases. In: GBR 2015, pp. 178–187 (2015)Google Scholar
  13. 13.
    Kotthoff, L., McCreesh, C., Solnon, C.: Portfolios of subgraph isomorphism algorithms. In: Festa, P., Sellmann, M., Vanschoren, J. (eds.) LION 2016. LNCS, vol. 10079, pp. 107–122. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-50349-3_8CrossRefGoogle Scholar
  14. 14.
    Solnon, C.: Solnon datasets (2017). http://liris.cnrs.fr/csolnon/SIP.html
  15. 15.
    Barabási, A.-L., Oltvai, Z.N.: Network biology: understanding the cell’s functional organization. Nat. Rev. Genet. 5(2), 101–113 (2004)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Information and Electrical Engineering and Applied MathematicsUniversity of SalernoFiscianoItaly

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