Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge

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Yaşar Üniversitesi E-Dergisi
Volume:14 Special Issue
Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge

Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge

Authors : Soraya SEDKAOUİ, Salim MOUALDİ

Pages : 25-32

View : 82 | Download : 6

Publication Date : 2019-03-27

Article Type : Research Paper

Abstract :Abstract The clustering method is one of the important methods that can be used to analyze the big volume of data that should be grouped accordingly as much as possible. Depending on the characteristics of the data available today and to deal with big data challenges, several clustering methods have been developed. But, in many situations, we cannot know a priori the number of clusters in the dataset. This refers to an important problem in cluster analysis or determining the numbers of clusters. In this context, this paper describes some clustering methods, with special attention to the Visual Assessment Tendency insert ignore into journalissuearticles values(VAT); algorithm as one of the known methods. This algorithm is implemented in advanced technologies to analyze big data. Keywords: Big data, clustering tendency, k-means, knowledge, visual assessment algorithm. JEL Codes: C10, C38
Keywords : Big data, clustering tendency, k means, knowledge, visual assessment algorithm

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