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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.2806
Subject(s) - multivariate statistics , computer science , data science , the internet , context (archaeology) , perspective (graphical) , multivariate analysis , big data , set (abstract data type) , focus (optics) , chemometrics , data mining , exploratory data analysis , artificial intelligence , machine learning , world wide web , geography , physics , optics , programming language , archaeology
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. Building on this parallelism, we review four classes of problems in networking: estimation, anomaly detection, optimization, and classification. We present an illustrative set of problems and show how a multivariate perspective may lead to significant improvements from state‐of‐the‐art techniques. In the absence of a better name, we call the approach of treating these problems from that multivariate perspective networkmetrics. Networkmetric problems have their own specificities, mainly, their typical Big Data nature and the presence of unstructured data. We argue that multivariate analysis is, indeed, useful to tackle these specificities. Copyright © 2016 John Wiley & Sons, Ltd.