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Information Quality in Information Fusion and Decision Making pp 519–538Cite as

Ranking Algorithms: Application for Patent Citation Network

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Part of the book series: Information Fusion and Data Science ((IFDS))

Abstract

How do technologies evolve in time? One way of answering this is by studying the US patent citation network. We begin this exploration by looking at macroscopic temporal behavior of classes of patents. Next, we quantify the influence of a patent by examining two major methods of ranking of nodes in networks: the celebrated “PageRank” and one of its extensions, reinforcement learning. A short history and a detailed explanation of the algorithms are given. We also discuss the influence of the damping factor when using PageRank on the patent network specifically in the context of rank reversal. These algorithms can be used to give more insight into the dynamics of the patent citation network. Finally, we provide a case study which combines the use of clustering algorithms with ranking algorithms to show the emergence of the opioid crisis. There is a great deal of data contained within the patent citation network. Our work enhances the usefulness of this data, which represents one of the important information quality characteristics. We do this by focusing on the structure and dynamics of the patent network, which allows us to determine the importance of individual patents without using any information about the patent except the citations to and from the patent.

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Acknowledgements

PE thanks the Henry Luce Foundation for support of Complex Systems Studies as Henry R Luce Professor. JT thanks the Herbert H. and Grace A. Dow Foundation for support as the Dow Distinguished Professor of the Natural Sciences.

Author information

Authors and Affiliations

  1. Center for Complex Systems, Kalamazoo College, Kalamazoo, MI, USA

    Hayley Beltz, Timothy Rutledge, Raoul R. Wadhwa & Péter Érdi

  2. ProcessExpert Ltd, Budapest, Hungary

    Péter Bruck

  3. Department of Physics, Kalamazoo College, Kalamazoo, MI, USA

    Jan Tobochnik

  4. Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest, Hungary

    Anikó Fülöp

  5. Poliphon Ltd., Budapest, Hungary

    György Fenyvesi

Authors
  1. Hayley Beltz
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  2. Timothy Rutledge
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  3. Raoul R. Wadhwa
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  4. Péter Bruck
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  5. Jan Tobochnik
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  6. Anikó Fülöp
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  7. György Fenyvesi
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  8. Péter Érdi
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Correspondence to Péter Érdi .

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Editors and Affiliations

  1. IMT-Atlantique, Brest, France

    Éloi Bossé

  2. The State University of New York at Buffalo, Buffalo, NY, USA

    Galina L. Rogova

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Beltz, H. et al. (2019). Ranking Algorithms: Application for Patent Citation Network. In: Bossé, É., Rogova, G. (eds) Information Quality in Information Fusion and Decision Making. Information Fusion and Data Science. Springer, Cham. https://doi.org/10.1007/978-3-030-03643-0_21

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  • DOI: https://doi.org/10.1007/978-3-030-03643-0_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03642-3

  • Online ISBN: 978-3-030-03643-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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