Clustering and ranking university majors using data mining and AHP algorithms: A case study in Iran

Although all university majors are prominent, and the necessity of their presence is of no question, they might not have the same priority basis considering different resources and strategies that could be spotted for a country. Their priorities likely change as the time goes by; that is, different majors are desirable at different time. If the government is informed of which majors could tackle today existing problems of world and its country, it surely more esteems those majors. This paper considers the problem of 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, we rank university majors.