Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran

Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran

چکیده

Abstract: Although all university majors are prominent and the necessity of their presences is of no question, they might not have the same priority basis considering different resources and strategies that could be spotted for a country. This paper focuses on clustering and ranking university majors in Iran. To do so, a model is presented to clarify the procedure. Eight different criteria are determined, and 177 existing university majors are compared on these criteria. First, by K-means algorithm, university majors are clustered based on similarities and differences. Then, by AHP algorithm, university majors are ranked.

کلیدواژه‌ها

data mining

clustering

K-means algorithm

multi-criteria decision making

analytic hierarchy process

university major ranking problem

عنوان مقاله English