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The bibliographic coupling approach to filter the cited and uncited patent citations: a case of electric vehicle technology

Author

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  • Hsi-Yin Yeh

    (National Taiwan University)

  • Yi-Shan Sung

    (National Taiwan University)

  • Hsiao-Wen Yang

    (National Taiwan University)

  • Wan-Chu Tsai

    (National Taiwan University)

  • Dar-Zen Chen

    (National Taiwan University)

Abstract

Because some cited references are not relevant to the citing patent and not all the relevant references are cited, the study attempts to use the bibliographic coupling (BC) approach to filter the irrelevant patent citations and supplement the relevant uncited patent citations to construct a patent citation network (PCN). The study selected the field of electric vehicle technology to explore the phenomenon and examined the characteristics of PCNs in terms of the average BC strength and the average citation time lag. Four PCNs were constructed in this study. The aggregated PCN (APCN) excluded the irrelevant patent citations and added the relevant uncited patent citations, which has brought out significant improvement. The APCN became more concentrated and the information which reserved in the APCN was the most current. Additionally, some invisible technology clusters and relationships were also manifested in the APCN.

Suggested Citation

  • Hsi-Yin Yeh & Yi-Shan Sung & Hsiao-Wen Yang & Wan-Chu Tsai & Dar-Zen Chen, 2013. "The bibliographic coupling approach to filter the cited and uncited patent citations: a case of electric vehicle technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 75-93, January.
  • Handle: RePEc:spr:scient:v:94:y:2013:i:1:d:10.1007_s11192-012-0820-8
    DOI: 10.1007/s11192-012-0820-8
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    Cited by:

    1. H. Simon & N. Sick, 2016. "Technological distance measures: new perspectives on nearby and far away," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1299-1320, June.
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    3. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    4. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.
    5. Huang, Mu-Hsuan & Yang, Hsiao-Wen & Chen, Dar-Zen, 2015. "Increasing science and technology linkage in fuel cells: A cross citation analysis of papers and patents," Journal of Informetrics, Elsevier, vol. 9(2), pages 237-249.
    6. Kuan, Chung-Huei & Huang, Mu-Hsuan & Chen, Dar-Zen, 2018. "Missing links: Timing characteristics and their implications for capturing contemporaneous technological developments," Journal of Informetrics, Elsevier, vol. 12(1), pages 259-270.
    7. Xiaoling Sun & Kun Ding, 2018. "Identifying and tracking scientific and technological knowledge memes from citation networks of publications and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1735-1748, September.

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