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Identifying missing relevant patent citation links by using bibliographic coupling in LED illuminating technology

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  • Chen, Dar-Zen
  • Huang, Mu-Hsuan
  • Hsieh, Hui-Chen
  • Lin, Chang-Pin

Abstract

This study uses bibliographic coupling to identify missing relevant patent links, in order to construct a comprehensive citation network. Missing citation links can be added by taking the missing relevant patent links into account. The Pareto principle is used to determine the threshold of bibliographic coupling strength, in order to identify the missing relevant patent links. Comparisons between the original patent citation network and the comprehensive patent citation network with the missing relevant patent links are illustrated at both the patent and assignee levels. Light emitting diode (LED) illuminating technology is chosen as the case study. The relationships between the patents and the assignees are obviously enhanced after adding the missing relevant patent links. The results show that the growth rates on both the total number and the average number of links have apparently improved at the patent level. At the assignee level, the number of linked assignees and the average number of links between two assignees are increased. The differences between the two citation networks are further examined by means of the Freeman vertex betweenness centrality and Johnson's hierarchical clustering. The patents with more new links to other patents have distinct results in terms of the Freeman vertex betweenness centrality. The enhancement of links among patents also results in different clustering.

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  • Chen, Dar-Zen & Huang, Mu-Hsuan & Hsieh, Hui-Chen & Lin, Chang-Pin, 2011. "Identifying missing relevant patent citation links by using bibliographic coupling in LED illuminating technology," Journal of Informetrics, Elsevier, vol. 5(3), pages 400-412.
    • Handle: RePEc:eee:infome:v:5:y:2011:i:3:p:400-412
    DOI: 10.1016/j.joi.2011.02.005
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    3. Huang, Ying & Chen, Lixin & Zhang, Lin, 2020. "Patent citation inflation: The phenomenon, its measurement, and relative indicators to temper its effects," Journal of Informetrics, Elsevier, vol. 14(2).
    4. Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
    5. Kuan, Chung-Huei & Chen, Dar-Zen & Huang, Mu-Hsuan, 2019. "Bibliographically coupled patents: Their temporal pattern and combined relevance," Journal of Informetrics, Elsevier, vol. 13(4).
    6. Kuan, Chung-Huei & Lin, Jia-Tian & Chen, Dar-Zen, 2021. "Characterizing Patent Assignees by Their Structural Positions Relative to a Field’s Evolutionary Trajectory," Journal of Informetrics, Elsevier, vol. 15(4).
    7. García-Lillo, Francisco & Seva-Larrosa, Pedro & Sánchez-García, Eduardo, 2023. "What is going on in entrepreneurship research? A bibliometric and SNA analysis," Journal of Business Research, Elsevier, vol. 158(C).
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    9. Wang, Xiaoli & Daim, Tugrul & Huang, Lucheng & Li, Zhiqiang & Shaikh, Ruqia & Kassi, Diby Francois, 2022. "Monitoring the development trend and competition status of high technologies using patent analysis and bibliographic coupling: The case of electronic design automation technology," Technology in Society, Elsevier, vol. 71(C).
    10. Zhang, Jin & Liu, Guannan & Ren, Ming, 2016. "Finding a representative subset from large-scale documents," Journal of Informetrics, Elsevier, vol. 10(3), pages 762-775.
    11. 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.
    12. 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.
    13. Chunjuan Luan & Haiyan Hou & Yongtao Wang & Xianwen Wang, 2014. "Are significant inventions more diversified?," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 459-470, August.
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