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The advent of big data leads to many applications of Machine Learning techniques. University rankings is one of the applicable domains, which is currently playing a crucial role in the assessment of the universities' performance. Currently, the rankings are usually carried out by some authoritative ranking institutions by means of weighting techniques and the results are conveyed in numerical rankings. Three of the most famous university ranking institutions have been introduced from a technical perspective. However, these institutions have been proven to be subjective in relation to their data selection and weighting method.
Li, Zhengshuo. (2019). Hierarchical Cluster Analysis: A New Type of Ranking Criteria Based on ARWU Ranking Data. M.Sc. in Computing (Data Analytics).