Document Details

Document Type : Article In Journal 
Document Title :
Comparison Between Data Clustering Algorithm
مقارنة ما بين خوارزميات تقسيم البيانات
 
Subject : Computer Science 
Document Language : English 
Abstract : Clustering is a division of data into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar compared to objects of other groups. This paper is intended to study and compare different data clustering algorithms. The algorithms under investigation are: K-means algorithm, Hierarchical Clustering algorithm, Self-Organizing Maps (SOMs) algorithm, and Expectation Maximization (EM) Clustering algorithm. All these algorithms are compared according to the following factors: size of dataset, number of clusters, type of dataset and type of software used. Some conclusions that are extracted belong to the performance, quality and accuracy of the clustering algorithms. 
ISSN : 1683-3198 
Journal Name : he International Arab Journal of Information Technology 
Volume : 5 
Issue Number : 3 
Publishing Year : 1428 AH
2008 AD 
Article Type : Article 
Added Date : Sunday, January 30, 2011 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
أسامه ابو عباسAbu Abbas, Osama InvestigatorMasterabuabbas@hotmail.com

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 28811.pdf pdfComparisons Between Data Clustering Algorithms

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