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Big Data Reduction and Visualization Using the K-Means Algorithm

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dc.contributor.author Akyol, Hakan
dc.contributor.author Kızılduman, Hale Sema
dc.contributor.author Dökeroğlu, Tansel
dc.date.accessioned 2024-02-14T07:49:02Z
dc.date.available 2024-02-14T07:49:02Z
dc.date.issued 2022-07
dc.identifier.citation Akyol, H.; Kızılduman, H.S.; Dökeroğlu, T. (2022). "Big Data Reduction and Visualization Using the K-Means Algorithm", Ankara Science University, Researcher, Vol.2, No.1., pp.40-45. tr_TR
dc.identifier.issn 2717-9494
dc.identifier.uri http://hdl.handle.net/20.500.12416/7194
dc.description.abstract A huge amount of data is being produced every day in our era. In addition to high-performance processing approaches, efficiently visualizing this quantity of data (up to Terabytes) remains a major difficulty. In this study, we use the well-known clustering method K-means as a data reduction strategy that keeps the visual quality of the provided huge data as high as possible. The centroids of the dataset are used to display the distribution properties of data in a straightforward manner. Our data comes from a recent Kaggle big data set (Click Through Rate), and it is displayed using Box plots on reduced datasets, compared to the original plots. It is discovered that K-means is an effective strategy for reducing the amount of huge data in order to view the original data without sacrificing its distribution information quality tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.55185/researcher.1135824 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Big Data tr_TR
dc.subject Data Reduction tr_TR
dc.subject Visualization tr_TR
dc.subject K-Means tr_TR
dc.title Big Data Reduction and Visualization Using the K-Means Algorithm tr_TR
dc.type article tr_TR
dc.relation.journal Ankara Science University, Researcher tr_TR
dc.contributor.authorID 234173 tr_TR
dc.identifier.volume 2 tr_TR
dc.identifier.issue 1 tr_TR
dc.identifier.startpage 40 tr_TR
dc.identifier.endpage 45 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Yazılım Mühendisliği Bölümü tr_TR


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