Next Article in Journal
LPaaS as Micro-Intelligence: Enhancing IoT with Symbolic Reasoning
Previous Article in Journal / Special Issue
EMG Pattern Recognition in the Era of Big Data and Deep Learning
Article Menu

Export Article

Open AccessArticle
Big Data Cogn. Comput. 2018, 2(3), 22; https://doi.org/10.3390/bdcc2030022

The Rise of Big Data Science: A Survey of Techniques, Methods and Approaches in the Field of Natural Language Processing and Network Theory

1
Department of Computer Science, Edge Hill University, Ormskirk, L39 4QP, UK
2
Department of Department of Electronics, Computing and Mathematics, University of Derby, Derby DE22 1GB, UK
3
Department of Computer Science and Information Systems, Birkbeck University of London, London WC1E 7HX, UK
*
Author to whom correspondence should be addressed.
Received: 30 May 2018 / Revised: 29 July 2018 / Accepted: 31 July 2018 / Published: 2 August 2018
(This article belongs to the Special Issue Big Data and Cognitive Computing: Feature Papers 2018)
View Full-Text   |   Download PDF [446 KB, uploaded 2 August 2018]   |  

Abstract

The continuous creation of data has posed new research challenges due to its complexity, diversity and volume. Consequently, Big Data has increasingly become a fully recognised scientific field. This article provides an overview of the current research efforts in Big Data science, with particular emphasis on its applications, as well as theoretical foundation. View Full-Text
Keywords: Big Data; text mining; NLP; network theory; Bayesian networks Big Data; text mining; NLP; network theory; Bayesian networks
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Ray, J.; Johnny, O.; Trovati, M.; Sotiriadis, S.; Bessis, N. The Rise of Big Data Science: A Survey of Techniques, Methods and Approaches in the Field of Natural Language Processing and Network Theory. Big Data Cogn. Comput. 2018, 2, 22.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Big Data Cogn. Comput. EISSN 2504-2289 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top