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The effect of patent family information in patent citation network analysis: a comparative case study in the drivetrain domain

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Abstract

Previous researchers of citation analysis often analyze patent data of a single authority because of the availability of the data and the simplicity of analysis. Patent analysis, on the other hand, is used not only for filing and litigation, but also for technology trend analysis. However, global technology trends cannot be understood only with the analysis of patent data issued by a single authority. In this paper, we propose the use of patents from multiple authorities and discuss the effect of bundling patent family information. We investigate the effect of patent families with cases from automobile drivetrain technology. Based on the results, we conclude that the use of multiple authorities’ patent data bundled with the patent family information can significantly improve the coverage and practicability of patent citation analysis.

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Notes

  1. In this paper , Mr. Osawa, an expert in the domain of drivetrain technology and one of the authors of this paper, attributes meaning to the clusters based on the patents they contain.

  2. The frequency of word i in Cluster s (FreWsi) was evaluated using the following formula:

    $${\text{FreW}}_{{\text{si}}} = \frac{{n_{\text{s}} }}{{n_{\text{s}} }}{ \times }\log \left( {\frac{N}{{N_{\text{i}} }}} \right)$$

    Here, n si represents the number of word i that appeared in the DWPI title and the abstract of the patents of Cluster s obtained in citation analysis. n s represents the number of words that appeared in the title and the abstract of patents of Cluster s. N is the number of clusters in total. N i is the number of clusters in which a patent contains the word i in the title and the abstract.

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Acknowledgments

A part of this research was carried out by the joint research program of the University of Tokyo and Toyota Central R&D Lab.

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Authors and Affiliations

  1. Center for Aviation Innovation Research (CAIR), The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan

    Hiroko Nakamura & Shinji Suzuki

  2. Graduate School of Innovation Management, Tokyo Institute of Technology, Tokyo, Japan

    Yuya Kajikawa

  3. Toyota Central R&D Lab, Aichi, Japan

    Masataka Osawa

Authors
  1. Hiroko Nakamura
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  2. Shinji Suzuki
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  3. Yuya Kajikawa
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  4. Masataka Osawa
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Correspondence to Hiroko Nakamura.

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Nakamura, H., Suzuki, S., Kajikawa, Y. et al. The effect of patent family information in patent citation network analysis: a comparative case study in the drivetrain domain. Scientometrics 104, 437–452 (2015). https://doi.org/10.1007/s11192-015-1626-2

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