Journal of Yaşar University

Journal of Yaşar University

Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge

Yazarlar: Soraya SEDKAOUİ, Salim MOUALDİ

Cilt 14 , Sayı - , 2019 , Sayfalar 25 - 32

Konular:Sosyal

Anahtar Kelimeler:Big data,Clustering tendency,K-means,Knowledge,Visual assessment algorithm

Özet: 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 (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

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@article{2019, title={Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge}, volume={14}, publisher={Journal of Yaşar University}, author={Soraya SEDKAOUİ,Salim MOUALDİ}, year={2019}, pages={25–32} }
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Soraya SEDKAOUİ,Salim MOUALDİ. (2019). Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge (Vol. 14, pp. 25–32). Vol. 14, pp. 25–32. Journal of Yaşar University.
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Soraya SEDKAOUİ,Salim MOUALDİ. Clustering Assessment Tendency for Big Data Analytics Extract Useful Knowledge. Journal of Yaşar University, 2019, pp. 25–32.
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