Title :
A study on educational data clustering approach based on improved particle swarm optimizer
Author :
Xiangwei Zheng ; Yuanjiang Jia
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
Abstract :
More and more clustering approaches are used in educational data mining for too many data are generated by web-based educational systems. To deal with the problem of premature convergence of the traditional K-means algorithm and computational costs, an improved K-means clustering algorithm based cooperative PSO frame is proposed in this paper. Cooperative PSO has been proved effective for large scale and complex problems via a divide-and-conquer strategy by simulating coevolutionary techniques in nature. Therefore, K-means clustering algorithm based cooperative PSO frame is effective in educational data clustering.
Keywords :
computer aided instruction; particle swarm optimisation; pattern clustering; PSO frame; Web-based educational systems; educational data clustering approach; educational data mining; improved K-means clustering algorithm; improved particle swarm optimizer; Algorithm design and analysis; Clustering algorithms; Data mining; Educational institutions; Particle swarm optimization; Partitioning algorithms; Vectors; K-Means; data clustering; particle swarm optimizer;
Conference_Titel :
IT in Medicine and Education (ITME), 2011 International Symposium on
Conference_Location :
Cuangzhou
Print_ISBN :
978-1-61284-701-6
DOI :
10.1109/ITiME.2011.6132144