Abstract
At present, one of the main ways to gauge the quality of a researcher is to use his or her h-index, which is defined as the largest integer n such that the researcher has at least n publications each of which has at least n citations. The fact that this quantity is widely used indicates that h-index indeed reasonably adequately describes the researcher’s quality. So, this notion must capture some intuitive idea. However, the above definition is not intuitive at all, it sound like a somewhat convoluted mathematical exercise. So why is h-index so efficient? In this paper, we use known mathematical facts about h-index—in particular, the results of its fuzzy-related analysis—to come up with an intuitive explanation for the h-index’s efficiency.
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Acknowledgements
This work was supported in part by the National Science Foundation via grants 1623190 (A Model of Change for Preparing a New Generation for Professional Practice in Computer Science) and HRD-1242122 (Cyber-ShARE Center of Excellence).
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Kreinovich, V., Kosheleva, O., Nguyen, H.P. (2021). Why h-Index. In: Kreinovich, V., Hoang Phuong, N. (eds) Soft Computing for Biomedical Applications and Related Topics. Studies in Computational Intelligence, vol 899. Springer, Cham. https://doi.org/10.1007/978-3-030-49536-7_6
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DOI: https://doi.org/10.1007/978-3-030-49536-7_6
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