Quantifying individual scientific output in terms of a new intuitionistic fuzzy sets based author-level metrics (IFALM)

Vassia Atanassova
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Abstract

The present paper proposes the idea of formulating a new author-level citation metrics, quantifying the individual’s scientific output, which uses the concept of intuitionistic fuzzy sets. This new metrics gives more visibility to the proportion of direct self-citations and hidden (co-author or collaborative) self-citations in the form of an intuitionistic fuzzy pair. Examples are given retrieving the necessary information from Scopus, one of the largest databases of peer-reviewed literature, which algorithmically enables retrieval of one’s citations including and excluding their own or their co-authors’ self-citations, as well as the calculation of three different values of one’s h-index with and without these respectively. Linear and triangular graphical representations are given, as well as comparisons with the concept proposed in 2005 by Jorge E. Hirsch, the now famous h-index, and ideas for future elaboration of the concept of the new intuitionistic fuzzy sets based author-level metrics, or shortly IFALM.
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用一种新的基于直觉模糊集的作者水平度量(IFALM)来量化个人科学产出
本文利用直觉模糊集的概念,提出了一种新的作者级被引指标,对个人的科学产出进行量化。这种新的度量标准以直观模糊对的形式提供了对直接自引用和隐藏(共同作者或协作)自引用比例的更多可见性。本文给出了从Scopus检索必要信息的例子,Scopus是最大的同行评审文献数据库之一,它通过算法可以检索一个人的引用,包括和不包括他们自己或共同作者的自引用,以及计算一个人的h-index的三个不同值,分别是有和没有这些值。给出了线性和三角形图形表示,并与2005年由Jorge E. Hirsch提出的概念进行了比较,即现在著名的h指数,以及对未来阐述基于作者水平度量(简称IFALM)的新直觉模糊集概念的想法。
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