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Semantic fingerprints-based author name disambiguation in Chinese documents

Author

Listed:
  • Hongqi Han

    (Institute of Scientific and Technical Information of China)

  • Changqing Yao

    (Institute of Scientific and Technical Information of China)

  • Yuan Fu

    (Institute of Scientific and Technical Information of China)

  • Yongsheng Yu

    (Institute of Scientific and Technical Information of China)

  • Yunliang Zhang

    (Institute of Scientific and Technical Information of China)

  • Shuo Xu

    (Institute of Scientific and Technical Information of China)

Abstract

Author name disambiguation is an important problem that needs to be resolved in bibliometric analysis or tech mining. Many techniques have been presented; however, most of them require a long run time or additional information. A new method based on semantic fingerprints was presented to disambiguate author names without external data. A manually annotated dataset was built to testify on the efficiency of the presented method. Experiments using co-author features, institution features, and text fingerprints were conducted respectively. We found that the first two methods had higher precision, but their recall was low, and the text fingerprint method had higher recall and satisfied precision. Based on these results, we integrated co-author features, institution features, and text fingerprints to provide semantic fingerprints for disambiguating author names and achieving better performance on the F-measure.

Suggested Citation

  • Hongqi Han & Changqing Yao & Yuan Fu & Yongsheng Yu & Yunliang Zhang & Shuo Xu, 2017. "Semantic fingerprints-based author name disambiguation in Chinese documents," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1879-1896, June.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2338-6
    DOI: 10.1007/s11192-017-2338-6
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    References listed on IDEAS

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    1. Anne-Wil Harzing, 2015. "Health warning: might contain multiple personalities—the problem of homonyms in Thomson Reuters Essential Science Indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2259-2270, December.
    2. Li Tang & John P. Walsh, 2010. "Bibliometric fingerprints: name disambiguation based on approximate structure equivalence of cognitive maps," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 763-784, September.
    3. Feriha Ibriyamova & Samuel Kogan & Galla Salganik-Shoshan & David Stolin, 2017. "Using semantic fingerprinting in finance," Applied Economics, Taylor & Francis Journals, vol. 49(28), pages 2719-2735, June.
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    Cited by:

    1. Jinseok Kim, 2019. "A fast and integrative algorithm for clustering performance evaluation in author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 661-681, August.
    2. Wang, Zhiqi & Chen, Yue & Glänzel, Wolfgang, 2020. "Preprints as accelerator of scholarly communication: An empirical analysis in Mathematics," Journal of Informetrics, Elsevier, vol. 14(4).
    3. Li Zhang & Wei Lu & Jinqing Yang, 2023. "LAGOS‐AND: A large gold standard dataset for scholarly author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(2), pages 168-185, February.
    4. YIN Deyun & MOTOHASHI Kazuyuki, 2018. "Inventor Name Disambiguation with Gradient Boosting Decision Tree and Inventor Mobility in China (1985-2016)," Discussion papers 18018, Research Institute of Economy, Trade and Industry (RIETI).
    5. Deyun Yin & Kazuyuki Motohashi & Jianwei Dang, 2020. "Large-scale name disambiguation of Chinese patent inventors (1985–2016)," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 765-790, February.
    6. Shuo Xu & Ling Li & Xin An, 2023. "Do academic inventors have diverse interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1023-1053, February.
    7. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).

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