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Visual analytics for big data using R

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dc.contributor.authorNasridinov A.-
dc.contributor.authorPark Y.-H.-
dc.date.available2021-02-22T10:57:27Z-
dc.date.issued2013-09-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/6520-
dc.description.abstractThe growth in volumes of data has affected today's large organization, where commonly used software tools to capture, manage, and process the data cannot handle big data effectively. The main challenge is that organizations must analyze a large amount of big data and extract useful information or knowledge for future actions in a short time. This type of demands has produced the markets for various innovative big data control mechanisms, such as visual analytics for big data. In this paper, we propose to visually analyze the big data using R statistical software. The proposed method is composed of three steps. In the first step, we extract the data set from the target website. In the second step, we parse the extracted raw data according to the types, and store in a database. In the third, we perform visual analysis from the stored data in database using R statistical software. © 2013 IEEE.-
dc.format.extent2-
dc.language영어-
dc.language.isoENG-
dc.titleVisual analytics for big data using R-
dc.typeArticle-
dc.identifier.doi10.1109/CGC.2013.96-
dc.identifier.scopusid2-s2.0-84893297399-
dc.identifier.bibliographicCitation2013 International Conference on Cloud and Green Computing, pp 564 - 565-
dc.citation.title2013 International Conference on Cloud and Green Computing-
dc.citation.startPage564-
dc.citation.endPage565-
dc.type.docTypeConference Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordPlusBig datum-
dc.subject.keywordPlusData set-
dc.subject.keywordPlusLarge amounts-
dc.subject.keywordPlusLarge organizations-
dc.subject.keywordPlusStatistical software-
dc.subject.keywordPlusVisual analysis-
dc.subject.keywordPlusVisual analytics-
dc.subject.keywordPlusVisualization-
dc.subject.keywordPlusData visualization-
dc.subject.keywordAuthorBig data-
dc.subject.keywordAuthorR statistical software-
dc.subject.keywordAuthorVisual analytics-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/6686088-
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