A Comparative Ranking Model among Mexican Universities Using Pattern Recognition

The evaluation of quality in higher education is today a matter great importance most countries because the allocation resources should be accordance with universities. Due to this, there are numerous initiatives create instruments and tools that can offer comparison among institutions countries, results these efforts used called international rankings. These rankings include some “reputational” or subjective, based on opinion polls applied groups that, which estimated, issue authorized views. There also “objective” rankings, performance indicators, calculated from certain set empirical data; however, many occasions indicators sponsored by universities desire appear best emphasize characteristics more than others, makes them untrustworthy very variable between each other. In this sense, we considered Comparative Study Mexican Universities (CSMU), database statistical information research institutions, allows users responsible for establishing comparisons relationships may exist existing items, building their own needs analysis perspectives (Márquez, 2010). This work develops an unsupervised alternative model ranking using pattern recognition, specifically clustering techniques, public access data. CSMU obtained analyzing 60 as first iteration, but present final UNAM excluded.