Selecting the right MBA schools – An application of self-organizing map networks

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摘要

The self-organizing map (SOM) network, an unsupervised neural computing network, is a categorization network developed by Kohonen. The SOM network was designed for solving problems that involve tasks such as clustering, visualization, and abstraction. In this study, we apply the clustering and visualization capabilities of SOM to group and plot the top 79 MBA schools as ranked by US News and World Report (USN&WR) into a two-dimensional map with four segments. The map should assist prospective students in searching for the MBA programs that best meet their personal requirements. Comparative analysis with the outputs from two popular clustering techniques K-means analysis and a two-step Factor analysis/K-means procedure are also included.

论文关键词:MBA ranking,Clustering,Kohonen SOM networks,Neural networks

论文评审过程:Available online 17 August 2007.

论文官网地址:https://doi.org/10.1016/j.eswa.2007.08.053