Big Data and Causality

Hossein Hassani (), Xu Huang and Mansi Ghodsi
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Hossein Hassani: Institute for International Energy Studies
Xu Huang: De Montfort University
Mansi Ghodsi: Institute for International Energy Studies

Annals of Data Science, 2018, vol. 5, issue 2, No 2, 133-156

Abstract: Abstract Causality analysis continues to remain one of the fundamental research questions and the ultimate objective for a tremendous amount of scientific studies. In line with the rapid progress of science and technology, the age of big data has significantly influenced the causality analysis on various disciplines especially for the last decade due to the fact that the complexity and difficulty on identifying causality among big data has dramatically increased. Data mining, the process of uncovering hidden information from big data is now an important tool for causality analysis, and has been extensively exploited by scholars around the world. The primary aim of this paper is to provide a concise review of the causality analysis in big data. To this end the paper reviews recent significant applications of data mining techniques in causality analysis covering a substantial quantity of research to date, presented in chronological order with an overview table of data mining applications in causality analysis domain as a reference directory.

Keywords: Big data; Data mining techniques; Causality analysis (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s40745-017-0122-3

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