An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis

Alfredo Cuzzocrea; Mohamed Medhat Gaber; Edoardo Fadda; Giorgio Mario Grasso

doi:10.1007/s12652-018-0966-1

An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis

Alfredo Cuzzocrea
, Mohamed Medhat Gaber
, Edoardo Fadda^*
, Giorgio Mario Grasso

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

17 Citations (SciVal)

Original language	English
Journal	Journal of Ambient Intelligence and Humanized Computing
DOIs	https://doi.org/10.1007/s12652-018-0966-1
Publication status	Published (VoR) - 13 Aug 2018

Keywords

Big data mining
Big environmental and atmospheric data
Clustering-based spatio-temporal analysis of big data

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10.1007/s12652-018-0966-1

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title = "An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis",

keywords = "Big data mining, Big environmental and atmospheric data, Clustering-based spatio-temporal analysis of big data",

author = "Alfredo Cuzzocrea and Gaber, \{Mohamed Medhat\} and Edoardo Fadda and Grasso, \{Giorgio Mario\}",

note = "Publisher Copyright: {\textcopyright} 2018, Springer-Verlag GmbH Germany, part of Springer Nature.",

year = "2018",

month = aug,

day = "13",

doi = "10.1007/s12652-018-0966-1",

language = "English",

journal = "Journal of Ambient Intelligence and Humanized Computing",

issn = "1868-5137",

publisher = "Springer",

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T1 - An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis

AU - Cuzzocrea, Alfredo

AU - Gaber, Mohamed Medhat

AU - Fadda, Edoardo

AU - Grasso, Giorgio Mario

PY - 2018/8/13

Y1 - 2018/8/13

KW - Big data mining

KW - Big environmental and atmospheric data

KW - Clustering-based spatio-temporal analysis of big data

UR - https://www.scopus.com/pages/publications/85051648219

UR - https://www.scopus.com/pages/publications/85051648219#tab=citedBy

U2 - 10.1007/s12652-018-0966-1

DO - 10.1007/s12652-018-0966-1

M3 - Article

AN - SCOPUS:85051648219

SN - 1868-5137

JO - Journal of Ambient Intelligence and Humanized Computing

JF - Journal of Ambient Intelligence and Humanized Computing

ER -

An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis

Keywords

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