Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran
Abstract
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.
Abbas Rad
Abolfazl Kazzazi
Mohammad Soltani
Davoud Talebi (1389). Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran. سال 5 (شماره 17), 113-134 Abbas Rad
Abolfazl Kazzazi
Mohammad Soltani
Davoud Talebi (2010). Mining and AHP algorithms: The case of Iran. Volume 5 (Number 17), 113-134
(2010). Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran. Iranian journal of management sciences, 5(Number 17), 113-134.
MLA
. "Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran". Iranian journal of management sciences, 5, Number 17, 2010, 113-134.
HARVARD
(2010). 'Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran', Iranian journal of management sciences, 5(Number 17), pp. 113-134.
VANCOUVER
Clustering and Ranking University Majors using Data Mining and AHP algorithms: The case of Iran. Iranian journal of management sciences, 2010; 5(Number 17): 113-134.
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