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Towards the Concept of Spatial Network Motifs

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Complex Networks and Their Applications XI (COMPLEX NETWORKS 2016 2022)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1078))

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Abstract

Many complex systems exist in the physical world and therefore can be modeled by networks in which their nodes and edges are embedded in space. However, classical network motifs only use purely topological information and disregard other features. In this paper we introduce a novel and general subgraph abstraction that incorporates spatial information, therefore enriching its characterization power. Moreover, we describe and implement a method to compute and count our spatial subgraphs in any given network. We also provide initial experimental results by using our methodology to produce spatial fingerprints of real road networks, showcasing its discrimination power and how it captures more than just simple topology.

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Notes

  1. 1.

    We will make available a github link to the source code if the paper is accepted.

References

  1. Barthélemy, M.: Spatial networks. Phys. Rep. 499(1–3), 1–101 (2011)

    Article  Google Scholar 

  2. Barthelemy, M.: Morphogenesis of spatial networks. Springer (2018)

    Google Scholar 

  3. Boguñá, M., Krioukov, D., Almagro, P., Serrano, M.Á.: Small worlds and clustering in spatial networks. Phys. Rev. Res. 2(2), 023040 (2020)

    Article  Google Scholar 

  4. Choobdar, S., Ribeiro, P., Silva, F.: Motif mining in weighted networks. In: 2012 IEEE 12th International Conference on Data Mining Workshops, pp. 210–217. IEEE (2012)

    Google Scholar 

  5. Grohe, M., Schweitzer, P.: The graph isomorphism problem. Commun. ACM 63(11), 128–134 (2020)

    Article  Google Scholar 

  6. Haklay, M., Weber, P.: Openstreetmap: user-generated street maps. IEEE Pervasive Comput. 7(4), 12–18 (2008)

    Article  Google Scholar 

  7. Hasan, S., Schneider, C.M., Ukkusuri, S.V., González, M.C.: Spatiotemporal patterns of urban human mobility. J. Stat. Phys. 151(1), 304–318 (2013)

    Article  MATH  Google Scholar 

  8. McKay, B.D., Piperno, A.: Practical graph isomorphism, ii. J. Symbol. Comput. 60, 94–112 (2014)

    Article  MATH  Google Scholar 

  9. Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., Alon, U.: Network motifs: simple building blocks of complex networks. Science 298(5594), 824–827 (2002)

    Article  Google Scholar 

  10. Narizuka, T., Yamamoto, K., Yamazaki, Y.: Statistical properties of position-dependent ball-passing networks in football games. Phys. A Stat. Mech. Appl. 412, 157–168 (2014)

    Article  MATH  Google Scholar 

  11. Newman, M.E.: The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003)

    Article  MATH  Google Scholar 

  12. Paranjape, A., Benson, A.R., Leskovec, J.: Motifs in temporal networks. In: Proceedings of the tenth ACM International Conference on Web Search and Data Mining, pp. 601–610 (2017)

    Google Scholar 

  13. Pržulj, N.: Biological network comparison using graphlet degree distribution. Bioinformatics 23(2), e177–e183 (2007)

    Article  Google Scholar 

  14. Ribeiro, P., Paredes, P., Silva, M.E., Aparicio, D., Silva, F.: A survey on subgraph counting: concepts, algorithms, and applications to network motifs and graphlets. ACM Comput. Surv. (CSUR) 54(2), 1–36 (2021)

    Article  Google Scholar 

  15. Ribeiro, P., Silva, F.: Discovering colored network motifs. In: Complex Networks V, pp. 107–118. Springer (2014)

    Google Scholar 

  16. Sallmen, S., Nurmi, T., Kivelä, M.: Graphlets in multilayer networks. J. Complex Netw. 10(2), cnac005 (2022)

    Google Scholar 

  17. Wernicke, S.: Efficient detection of network motifs. IEEE/ACM Trans. Comput. Biol. Bioinform. 3(4), 347–359 (2006)

    Article  Google Scholar 

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Acknowledgements

This work is partially financed financed by National Funds through the Portuguese funding agency, FCT—Fundação para a Ciência e a Tecnologia within project LA/P/0063/2020 and grant SFRH/BD/136525/2018. We would also like to thank the reviewers for the insightful comments.

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Correspondence to Pedro Ribeiro .

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Ferreira, J., Barbosa, A., Ribeiro, P. (2023). Towards the Concept of Spatial Network Motifs. In: Cherifi, H., Mantegna, R.N., Rocha, L.M., Cherifi, C., Micciche, S. (eds) Complex Networks and Their Applications XI. COMPLEX NETWORKS 2016 2022. Studies in Computational Intelligence, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-031-21131-7_44

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  • DOI: https://doi.org/10.1007/978-3-031-21131-7_44

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  • Print ISBN: 978-3-031-21130-0

  • Online ISBN: 978-3-031-21131-7

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