НАУКОМЕТРИЧЕН АНАЛИЗ В ОБЛАСТТА НА BIGDATA2
SCIENCEMETRIC ANALYSIS IN THE “BIG DATA” AREA

Author(s): Ivan Popchev, Milena Georgieva
Subject(s): Information Architecture, Electronic information storage and retrieval
Published by: Бургаски свободен университет
Keywords: Big data; data science; Data mining; Educational Data mining; Hadoop; MapReduce; Science direct; Google Scholar; Microsoft academic research; In memory computing
Summary/Abstract: The data which is generated and collected nowadays has a volume which requires developing a special paradigms. „Big Data” is the today’s buzzword. With the lowering the hardware prices more companies, are able to keep data bigger than Zeta bytes. The aim of this research is to follow how common the „Big data“ paradigm is. The work over this material was divided into three parts. During the first part ten different keywords were defined, which were used for a search in four popular scientific data bases. During the second stage of the research three new data bases were used and the keywords were consolidated. During the last stage of the research four new keywords were introduced. The aim of this research is to follow the development of the paradigm of “Big Data” during the last ten years through the methods of the sciencemetric.

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