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Strategies Comparison in Link Building Problem

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Intelligent Distributed Computing XIII (IDC 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 868))

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Abstract

Choosing an effective yet efficient solution to the link building problem means to select which nodes in a network should point a newcomer in order to increase its rank while limiting the cost of this operation (usually related to the number of such in-links). In this paper we consider different heuristics to address the question and we apply them both to Scale-Free (SF) and Erdős-Rényi (ER) networks, showing that the best tradeoff is achieved with the long-distance link approach, i.e. a newcomer node gathering farthest in-links succeeds in improving its position (rank) in the network with a limited cost.

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Acknowledgements

This work has been partially supported by the Università degli Studi di Catania, “Piano della Ricerca 2016/2018 Linea di intervento 2”.

Author information

Authors and Affiliations

  1. Dip. di Matematica e Informatica, Università degli Studi di Catania, Catania, Italy

    Vincenza Carchiolo

  2. Dip. Ingegneria Elettrica Elettronica Informatica, Università degli Studi di Catania, Catania, Italy

    Marco Grassia, Alessandro Longheu, Michele Malgeri & Giuseppe Mangioni

Authors
  1. Vincenza Carchiolo
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  2. Marco Grassia
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  3. Alessandro Longheu
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  4. Michele Malgeri
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  5. Giuseppe Mangioni
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Corresponding author

Correspondence to Giuseppe Mangioni .

Editor information

Editors and Affiliations

  1. SPIIRAS, St. Petersburg, Russia

    Igor Kotenko

  2. University of Craiova, Craiova, Romania

    Costin Badica

  3. SPIIRAS, St. Petersburg, Russia

    Vasily Desnitsky

  4. LAAS - CNRS, Toulouse Cedex 4, France

    Didier El Baz

  5. University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanovic

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Carchiolo, V., Grassia, M., Longheu, A., Malgeri, M., Mangioni, G. (2020). Strategies Comparison in Link Building Problem. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_23

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