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Networkmetrics: multivariate big data analysis in the context of the internet
Author(s) -
Camacho José,
MagánCarrión Roberto,
GarcíaTeodoro Pedro,
Treinen James J.
Publication year - 2016
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2829
Subject(s) - the internet , big data , data science , computer science , multivariate statistics , perspective (graphical) , context (archaeology) , focus (optics) , exploratory data analysis , multivariate analysis , analytics , data mining , world wide web , artificial intelligence , machine learning , geography , physics , archaeology , optics
Multivariate problems are found in all areas of knowledge. In chemistry and related disciplines. The chemometric community was developed in a joint effort to understand and solve problems mainly from a multivariate and exploratory perspective. This perspective is, indeed, of broader applicability, even in areas of knowledge far from chemistry. In this paper, we focus on the Internet: the net of devices that allow an interconnected world where all types of data can be shared and unprecedented communication services can be provided. Problems in the Internet, or, in general, in networking, are not very different from chemometric problems. Yet, they also have their specificities, mainly their typical Big Data nature and the presence of unstructured data. Exabytes of data in the format of text, video, audio, etc. are daily generated in the Internet. Part of these data need to be analyzed for disparate purposes, ranging from the optimization of the communications to cybersecurity and cyberwalfare. We argue that exploratory multivariate analysis is, indeed, useful to tackle these problems and has a role to play in the Big Data arena, currently limited to data mining techniques and visualization analytics. In absence of a better name, we call Networkmetrics the approach of treating Internet problems from the multivariate and exploratory perspective.