Aggregation World University Ranking Based on HITS

Yang Zhang, Yu Xiao, Jun Wu
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Abstract

Numerous university rankings have been propo sed in recent decades. Different methodology and indicators lead t he remarkable divergence among various rankings which confuses decisionmakers. In this pape r, we analyzed the difference between four wellknown world university rankings and confirm that the huge divergence makes it difficult to choose only one ranking as a standard. To solve this problem , we propose to generate a comprehensive world university ranking by aggregating existing individual university rankings using Hyperlink- induced topic search algorithm. It is shown that the ag gregated ranking just likes a ‘ cocktail ’ consisting of all the information from individual university rankings and can ef ficiently eliminate the outliers and regional partiality as a “ smoothe r ” .
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基于HITS的综合世界大学排名
近几十年来,人们提出了许多大学排名。不同的方法和指标导致各种排名之间的显著差异,使决策者感到困惑。在本文中,我们分析了四个世界知名大学排名之间的差异,并证实了巨大的差异使得很难只选择一个排名作为标准。为了解决这个问题,我们提出利用超链接诱导的主题搜索算法,通过汇总现有的单个大学排名来生成一个综合的世界大学排名。结果表明,综合排名就像一个“鸡尾酒”,由各个大学排名的所有信息组成,可以有效地消除异常值和地区偏见,作为一个“平滑r”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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