A Fuzzy-based Scoring Rule for Author Ranking

被引：0
|
作者：
Cardin, Marta [1 ]
Corazza, Marco [1 ]
Funari, Stefania [1 ]
Giove, Silvio [1 ]
机构：
[1] Ca Foscari Univ Venice, Venice, Italy
来源：
Neural Nets WIRN11 | 2011年 / 234卷
关键词：
Research evaluation; bibliometrics; author ranking; h-index; scoring rules; fuzzy inference system; HIRSCH-INDEX; H-INDEX; STANDS TODAY; JOURNALS; INDICATORS;
D O I：
10.3233/978-1-60750-972-1-36
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 la Sugeno.
引用
收藏
页码：36 / 45
页数：10
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