A Genetic Algorithm Approach to Partitioning Clustering: A Case Study on M.Sc. Applicants

Author

Lavangnananda, Kittichai ; Poolphol, Ratipong

Author_Institution

Sch. of Inf. Technol., King Mongkut´s Univ. of Technol. Thonburi, Bangkok, Thailand

fYear

2014

fDate

3-6 Dec. 2014

Firstpage

535

Lastpage

540

Abstract

Acquiring a Master Degree is becoming a common practice to ensure successful life and good career path, especially in developing countries. Master Degree in Information Technology is one of the most popular programmes with prolific number of applications and students. This work has two main objectives. First is to discover the number of clusters of applicants and the characteristics of each cluster. Another is to develop a Genetic Algorithm based Partitioning Clustering Program. This is achieved by incorporating distance matrix and its application in Divisive Analysis and Gower´s measure of similarity. The Genetic Algorithm based Partitioning Clustering program developed was proven superior to some common clustering techniques.

Keywords

computer aided instruction; computer science education; educational courses; further education; genetic algorithms; matrix algebra; Gower measure of similarity; M.Sc. applicant; Master Degree in Information Technology; distance matrix; divisive analysis; genetic algorithm; partitioning clustering program; Biological cells; Clustering algorithms; Educational institutions; Encoding; Genetic algorithms; Information technology; Prototypes; Clustering; Divisive Analysis; Genetic Algorithms; Gower´s Measure of Similarity; Master Degree in Information Technology; Partitioning Clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Applications (ICMLA), 2014 13th International Conference on

Conference_Location

Detroit, MI

Type

conf

DOI

10.1109/ICMLA.2014.93

Filename

7033172