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 theirpresences is of no question, they might not have the same priority basisconsidering different resources and strategies that could be spotted for acountry. their priorities likely change as time goes by; that is, differentmajors are desirable at different times. if the government is informed ofwhich majors could tackle today existing problems of the world and thecountry, it surely would esteem those majors more. this paper considersthe problem of clustering and ranking university majors in iran. to do so,a model is presented to clarify the procedure. eight different criteria aredetermined and 177 existing university majors are compared on thesecriteria. first, by k-means algorithm, university majors are clusteredbased on similarities and differences. then, by ahp algorithm, we rankuniversity majors.