Unsupervised author disambiguation using Dempster–Shafer theory
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DOI: 10.1007/s11192-014-1283-x
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References listed on IDEAS
- Milojević, Staša, 2013. "Accuracy of simple, initials-based methods for author name disambiguation," Journal of Informetrics, Elsevier, vol. 7(4), pages 767-773.
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Cited by:
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- 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.
- Rehs, Andreas, 2021. "A supervised machine learning approach to author disambiguation in the Web of Science," Journal of Informetrics, Elsevier, vol. 15(3).
- 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.
- Jinseok Kim & Jenna Kim, 2020. "Effect of forename string on author name disambiguation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(7), pages 839-855, July.
- KM. Pooja & Samrat Mondal & Joydeep Chandra, 2021. "Exploiting similarities across multiple dimensions for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7525-7560, September.
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Keywords
Author disambiguation; Dempster–Shafer theory of evidence; Hierarchical clustering; Unsupervised;All these keywords.
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