Irregular Trend Finder: Visualization tool for analyzing time-series big data

Takeda, Shinnosuke; Kobayashi, Aimi; Kobayashi, Hiroaki; Okubo, Saori; Misue, Kazuo

doi:10.1109/vast.2012.6400504

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2015

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“…There was an increase of more than 200 % from 2011 to 2012. This is due to a significant rise of works related to Big Data mining [4,72] and Big Data visualization [73,74]. Literature on Big Data had a growth of more than 150 % from 2012 to 2014.…”

Section: Classification Of Research Papersmentioning

confidence: 99%

A general perspective of Big Data: applications, tools, challenges and trends

et al. 2015

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Big Data has become a very popular term. It refers to the enormous amount of structured, semi-structured and unstructured data that are exponentially generated by high-performance applications in many domains: biochemistry, genetics, molecular biology, physics, astronomy, business, to mention a few. Since the literature of Big Data has increased significantly in recent years, it becomes necessary to develop an overview of the state-of-the-art in Big Data. This paper aims to provide a comprehensive review of Big Data literature of the last 4 years, to identify the main challenges, areas of application, tools and emergent trends of Big Data. To meet this objective, we have analyzed and classified 457 papers concerning Big Data. This review gives relevant B Giner Alor-Hernández

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Section: Classification Of Research Papersmentioning

confidence: 99%