A fuzzy-based scoring rule for author ranking
The measurement of the quality of research has reached nowadays an increasing interest not only for scientific reasons but also for the critical problem of researchers' ranking, due to the lack of grant assignments. The most commonly used approach is based on the so-called $h$-index, even if the current literature debated a lot about its pros and cons. This paper, after a brief review of the $h$-index and of alternative models, focuses on the characterization and the implementation of a modified scoring rule approach by means of a fuzzy inference system a l� Sugeno.
|Date of creation:||2011|
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- Denis Bouyssou & Thierry Marchant, 2011.
"Ranking scientists and departments in a consistent manner,"
Journal of the Association for Information Science & Technology,
Association for Information Science & Technology, vol. 62(9), pages 1761-1769, September.
- Denis Bouyssou & Thierry Marchant, 2011. "Ranking scientists and departments in a consistent manner," Post-Print hal-00606931, HAL.
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- Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
- Bouyssou, D. & Marchant, T., 2010. "Consistent bibliometric rankings of authors and of journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 365-378.
- Cabrerizo, F.J. & Alonso, S. & Herrera-Viedma, E. & Herrera, F., 2010. "q2-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the Hirsch core," Journal of Informetrics, Elsevier, vol. 4(1), pages 23-28. Full references (including those not matched with items on IDEAS)
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