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

机译:基于显性偏好方法的AI期刊排行榜开发

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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:这项研究对人工智能领域的179种学术期刊进行了排名。为此,利用了揭示的偏好方法(也称为引文影响方法)从Google学术搜索收集数据。排行榜是根据三个相对新颖的指数制定的:h指数,g指数和hc指数。这些指数彼此之间有着完美的关联,并且与汤姆森的《期刊影响因子》有着非常强的关联。想要展示自己的研究成果的学者,不熟悉AI研究领域的各种学术委员会,图书馆员和管理人员都可以使用所提供的清单。

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