Business Applications for Current Developments in Big Data Clustering: An Overview

被引:0
|
作者
Hass, G. [1 ]
Simon, P. [1 ]
Kashef, R. [2 ]
机构
[1] Western Univ, Ivey Business Sch, London, ON, Canada
[2] Ryerson Univ, Elect Comp & Biomed Engn Dept, Toronto, ON, Canada
关键词
Big Data; Analytics; Clustering Analysis; Business Applications; ALGORITHM;
D O I
10.1109/ieem45057.2020.9309941
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
"The world's most valuable resource is no longer oil, but data" announces the headline of the May 6th, 2017 edition of The Economist; the digital revolution is here to stay. The primary currency of this movement is big data. The complexity of big data is defined as the relationships and how the data can be arranged with one another. Facebook has 30 billion pieces of unique information shared each month; this data's sheer size can cause an immeasurable amount of combinations for relational data. Analyzing this big data can reveal various useful insights for decision-makers. With the adoption of clustering analysis, patterns and hidden information can be developed from big raw data that can be used across many business problems and applications. In this paper, an overview of the state of the art of clustering analysis and its adoption in business applications in the era of big data is presented.
引用
收藏
页码:195 / 199
页数:5
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