Abstract
University rankings are used all over the world to compare the quality and the prestige of universities. These rankings are usually based on combinations of arbitrarily weighted performance factors. This method has a number of shortcomings. To overcome these shortcomings, a cluster-based approach to university performance evaluation is proposed. Different data mining techniques are used to analyse the performance of UK universities based on the same data used to compile The Sunday Times University Guide 2010 league table and the results are compared with the original ranking. It is shown that clustering techniques, such as Self-Organizing Map or the k-means algorithm, can be used tosuccessfully classify universities in terms of performance.
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© 2010 Springer-Verlag London
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Nolle, L. (2010). Cluster-Based Benchmarking of Universities as an Alternative to League Tables. In: Bramer, M., Ellis, R., Petridis, M. (eds) Research and Development in Intelligent Systems XXVI. Springer, London. https://doi.org/10.1007/978-1-84882-983-1_40
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DOI: https://doi.org/10.1007/978-1-84882-983-1_40
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