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Node Matching Computation Between Two Large Graphs in Linear Computational Cost

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Graph-Based Representations in Pattern Recognition (GbRPR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10310))

Abstract

Error-tolerant graph matching has been demonstrated to be an NP-problem, for this reason, several sub-optimal algorithms have been presented with the aim of making the runtime acceptable in some applications. Some well-known sub-optimal algorithms have 6th, cubic or quadratic cost with respect to the order of the graphs. When applications deal with large graphs (social nets), these costs are not acceptable. For this reason, we present an error-tolerant graph-matching algorithm that it is linear with respect to the order of the graphs. Our method needs an initial seed, which is composed of one or several node-to-node mappings. The algorithm has been applied to analyse the friendship variability of social nets.

This research is supported by the spanish projects TIN2016-77836-C2-1-R and ColRobTransp MINECO DPI2016-78957-R AEI/FEDER EU.

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Authors and Affiliations

  1. Universitat Rovira i Virgili, Catalonia, Spain

    Pep Santacruz, Shaima Algabli & Francesc Serratosa

Authors
  1. Pep Santacruz
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  2. Shaima Algabli
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  3. Francesc Serratosa
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Corresponding author

Correspondence to Francesc Serratosa .

Editor information

Editors and Affiliations

  1. Università degli Studi di Salerno, Fisciano, Italy

    Pasquale Foggia

  2. Chinese Academy of Sciences, Beijing, China

    Cheng-Lin Liu

  3. Università degli Studi di Salerno, Fisciano, Italy

    Mario Vento

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Santacruz, P., Algabli, S., Serratosa, F. (2017). Node Matching Computation Between Two Large Graphs in Linear Computational Cost. In: Foggia, P., Liu, CL., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2017. Lecture Notes in Computer Science(), vol 10310. Springer, Cham. https://doi.org/10.1007/978-3-319-58961-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-58961-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58960-2

  • Online ISBN: 978-3-319-58961-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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