The Promotion of Graduate Programs through Clustering Prospective Students

The promotion of academic programs, particularly at graduate levels, emerges as a response to market changes. In general, graduate programs are not a first order necessity which makes necessary the right promotion of such programs guarantee the attraction of prospective students, which enroll in som...

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Main Authors: Rosa María Cantón Croda, Damián Emilio Gibaja Romero, Fernando-Rey Castillo-Villar
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2019-12-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
Online Access:http://www.ijimai.org/journal/node/3223
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spelling doaj-b65dd5db81ba49589fb160ff49737a632020-11-25T02:28:43ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602019-12-0156233210.9781/ijimai.2019.07.001ijimai.2019.07.001The Promotion of Graduate Programs through Clustering Prospective StudentsRosa María Cantón CrodaDamián Emilio Gibaja RomeroFernando-Rey Castillo-VillarThe promotion of academic programs, particularly at graduate levels, emerges as a response to market changes. In general, graduate programs are not a first order necessity which makes necessary the right promotion of such programs guarantee the attraction of prospective students, which enroll in some of them, which is essential for the financial sustainability of universities. Notably, the last one is a crucial problem for private universities. In this paper, we analyze the prospective students that enroll in a private to design better promotion strategies by using on data gathered by online sources. Specifically, we use clustering techniques to define marketing strategies based on segments of students. We find that age and city are crucial to promoting graduate programs while marital status and sex does not impact the decision of students in the university that we analyze.http://www.ijimai.org/journal/node/3223clusteringdecision-levelmachine learning
collection DOAJ
language English
format Article
sources DOAJ
author Rosa María Cantón Croda
Damián Emilio Gibaja Romero
Fernando-Rey Castillo-Villar
spellingShingle Rosa María Cantón Croda
Damián Emilio Gibaja Romero
Fernando-Rey Castillo-Villar
The Promotion of Graduate Programs through Clustering Prospective Students
International Journal of Interactive Multimedia and Artificial Intelligence
clustering
decision-level
machine learning
author_facet Rosa María Cantón Croda
Damián Emilio Gibaja Romero
Fernando-Rey Castillo-Villar
author_sort Rosa María Cantón Croda
title The Promotion of Graduate Programs through Clustering Prospective Students
title_short The Promotion of Graduate Programs through Clustering Prospective Students
title_full The Promotion of Graduate Programs through Clustering Prospective Students
title_fullStr The Promotion of Graduate Programs through Clustering Prospective Students
title_full_unstemmed The Promotion of Graduate Programs through Clustering Prospective Students
title_sort promotion of graduate programs through clustering prospective students
publisher Universidad Internacional de La Rioja (UNIR)
series International Journal of Interactive Multimedia and Artificial Intelligence
issn 1989-1660
1989-1660
publishDate 2019-12-01
description The promotion of academic programs, particularly at graduate levels, emerges as a response to market changes. In general, graduate programs are not a first order necessity which makes necessary the right promotion of such programs guarantee the attraction of prospective students, which enroll in some of them, which is essential for the financial sustainability of universities. Notably, the last one is a crucial problem for private universities. In this paper, we analyze the prospective students that enroll in a private to design better promotion strategies by using on data gathered by online sources. Specifically, we use clustering techniques to define marketing strategies based on segments of students. We find that age and city are crucial to promoting graduate programs while marital status and sex does not impact the decision of students in the university that we analyze.
topic clustering
decision-level
machine learning
url http://www.ijimai.org/journal/node/3223
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