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The Development of an AI Journal Ranking List Based on the Revealed Preference Approach

机译:基于透露偏好方法的AI期刊排列列表的开发

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This study presents a ranking of 179 academic journals in the field of artificial intelligence. For this, the revealed preference approach, also referred to as a citation impact method, was utilized to collect data from Google Scholar. The ranking list was developed based on three relatively novel indices: h-index, g-index, and hc-index. These indices correlated perfectly with one another, and they correlated very strongly with Thomson's Journal Impact Factors. The presented list may be utilized by scholars who want to demonstrate their research output, various academic committees, librarians and administrators who are not familiar with the AI research domain.
机译:本研究介绍了人工智能领域的179个学术期刊的排名。为此,利用所显示的偏好方法,作为引文影响方法,用于收集Google学者的数据。排名列表是基于三个相对新颖的指数开发的:H-Index,G-Index和HC索引。这些指数彼此完全相关,它们与汤姆森的日志影响因素非常强烈相关。该列表可以由想要展示其研究产出,不熟悉AI研究领域的各种学术委员会,图书馆员和管理员的学者使用。

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