Bulut bilişimde veri madenciliği tekniklerinin uygulanması: Bir literatür taraması

Year 2018, Volume: 24 Issue: 2, 336 - 343, 30.04.2018

Pelin Yıldırım Derya Birant

Abstract

Son
yıllarda, bilgi ve iletişim teknolojilerindeki yenilikler ve gelişmeler, analiz
edilmesi gereken veri miktarını önemli derecede artırmıştır. Büyük ölçekli
verilerin saklanması, yüksek hacimli verilerden veri madenciliği teknikleri ile
yararlı bilgilerin çıkartılması ve geleceğin tahminlenmesi maliyetli ve zorlu
işlemlerdir. Bu zorlukların üstesinden gelebilmek için, bilgi keşfi süreci;
bulut bilişim, paralel ve dağıtık hesaplama kullanılarak etkin bir şekilde
gerçekleştirilebilmektedir. Bu makale, bulut bilişimin ölçeklenebilirliği
sayesinde veri madenciliği algoritmalarının performanslarının arttırılabileceğini,
ayrıca her yerden ulaşılabilirlik, düşük maliyet ve kolay yönetilebilirlik
avantajlarının sağlanabileceğini göstermektedir. Makalede, bulut platformunda
gerçekleştirilen veri madenciliği uygulamaları; kullanılan metotlar, veriler ve
elde edilen sonuçlar çerçevesinde sunulmaktadır. Literatürde, bu konuda
önerilen çözüm yaklaşımları; sınıflandırma, kümeleme ve birliktelik kuralları
analizi olmak üzere üç ana kategori altında ele alınmaktadır.

Keywords

Veri madenciliği, Sınıflandırma, Kümeleme, Birliktelik kuralları analizi, Bulut bilişim

Application of data mining techniques in cloud computing: A literature review

Abstract

In
recent years, new innovations and developments in information and communication
technologies have hugely increased the quantity of data required to analyze.
Storing large-scale datasets, extracting useful knowledge from the huge volumes
of data by applying data mining techniques and predicting the future are costly
and difficult processes. To overcome these challenges, the knowledge discovery
process is performed efficiently by using cloud, parallel and distributed
computing. This article shows that the performance algorithms in data mining
can be increased by the scalability of cloud computing with the advantages in
terms of accessibility from anywhere, low cost and maintainability. In this
article, data mining applications that have been implemented on cloud platforms
are presented, including methods, data and obtained results. Solution
approaches that have been proposed related to this topic in the literature are
handled in three main categories: classification, clustering and association
rule mining.

Keywords

Data mining, Classification, Clustering, Association rule mining, Cloud computing

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