big data 2020


Big Data Technology can be defined as a Software-Utility that is designed to Analyse, Process and Extract the information from an extremely complex and large data sets which the Traditional Data Processing Software could never deal with.

Big social data approaches in Internet studies: The case of Twitter
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Abstract Well beyond Internet Studies itself, but arguably led by it to a considerable extent, there has been a turn towards computational methods in the study of social and communicative phenomena at large scale. This computational turn has commonly been The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data . To solve these problems, a group of new

Introduction to the Minitrack on Big Data on Healthcare Application
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The recent confluence of new technologies and dataintensive research methodologies offers a new research challenges for traditional research. High performance computing, client-cloud architecture, broadband networks, personal devices and sensors, multimedia

Biomedical Imaging and Analysis In the Age of Sparsity, Big Data , and Deep Learning
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IMAGING of the human body using a number of different modalities has revolutionized medicine over the past several decades and continues to grow at a rapid pace . More than ever, previously unknown information about biology and disease is being unveiled at a Internet research, and especially social media research, has benefited from concurrent factors, technological and analytical, that have enabled access to vast amounts of user data and content online. These trends have accompanied a prevalence of Big Data studies of Recently there has been much excitement about using big data in social research, especially data derived from digital media. This chapter examines leading examples of this type of research from three platforms: Facebook, Twitter, and Wikipedia. It discusses their

A Secured Demand Side Management Engine for Smart Societies using Industrial IoT and Big Data Analytics
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Smart societies have an increasing demand for quality-oriented services and infrastructure in an Industrial Internet of Things (IIoT) paradigm. Smart urbanization faces numerous challenges. Among them, secured energy Demand Side Management (DSM) is of particular

Introduction to the Minitrack on Artificial Intelligence and Big Data Analytics Management, Governance, and Compliance
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Artificial Intelligence (AI) and Big Data applications are becoming increasingly important strategic assets as they enable organizations to differentiate from their competitors by offering new data -driven products and services, by achieving increased agility in operations

Big Data and Academic Libraries: The Quest for Informed Decision-Making
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Tiffini A. Travis and Christian Ramirez abstract: Libraries remain one of the last places on campus where the purging of usage data is encouraged and tracking is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of

Introduction to the Minitrack on Big Data and Analytics: Pathways to Maturity
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The Big Data and Analytics minitrack of the Decision Analytics, Mobile Services, and Service Science has selected six papers to constitute this minitrack. This year the majority of papers focused on techniques for improving analytical approaches. Our first paper, Easy and

The Belmont Report in the Age of Big Data : Ethics at the Intersection of Psychological Science and Data Science
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My thanks to Tom Griffiths for conversations about related issues during our work together on Data on the Mind; to Julia Blau for invaluable feedback on this chapter; to Aaron Culich for thoughtful discussions about securing computational pipelines; to audiences at U

Introduction to the Minitrack on Business Intelligence and Big Data for Innovative and Sustainable Development of Organizations
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The development of the Internet, social media, distributed databases, and a variety of mobile devices has caused a huge increase in data . Much of this diverse data in unstructured and structured forms has a high business value and, if properly utilized, can become anIn the original version of this book, the author name Ahmed M. Mithon has been changed to Ahamed. M Mithun . The chapter and book have been updated with the changes The updated

Introduction to the Minitrack on Social Media Management in Big Data Era
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Social media can be a powerful means of disseminating public opinions and personalized preferences on products, events, service, etc. Advances in big data analytical techniques make it possible for organizations to better understand the mechanisms of brand-related

Assessing Big Data Analytics Capability and Sustainability in Supply Chains
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Big data analytics capability (BDAC) is a technologybased capability, which can influence sustainability performance of firms in supply chains. By using BDAC strategically, supply chains could improve their responses to social, environmental, and social changes taking Fig. 2.1 Manuscripts temporal distribution 20 Fig. 2.2 VOSviewer result 27 Fig. 3.1 Market capitalizing agility and operational adjustment agility and their role in shaping an agile organization (Source Authors elaboration) 48 Fig. 3.2 The importance of BDA capable

Big data analytics and sustainable textile manufacturing: Decision-making about the applications of biotechnologies in developing countries Management
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Purpose: This article discusses issues associated with the application Big Data Analytics for decision-making about the introduction of new technologies in the textile industry in the developing world. Methodology: We use the LMX theoretical framework to consider the

Classification algorithms for Big Data
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A classification algorithm is a versatile tool, that can serve as a predictor for the future or as an analytical tool to understand the past. Several obstacles prevent classification from scaling to a large Volume, Velocity, Variety or Value. The aim of this thesis is to scale The last three decades have seen a surge in data collection. During the same period, statisticians and econometricians have developed numerous techniques to digest the ever- growing amount of data and improve predictions. This volume surveys the adaptation of

AReview ON THE SIGNIFICANCE OF MACHINE LEARNING FOR DATA ANALYSIS IN BIG DATA
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Big data revolution is changing the lifestyle in terms of working and thinking environments through facilitating improvement in vision finding and decision-making. But, big data sciences technical dilemma is that there is no knowledge that can administer and analyze

Elektronische Supplemente zu: Big Data in der Radikalisierungsforschung: Eine systematische Übersichtsarbeit
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1. BACKGROUND ZPID-Leibniz Institute for Psychology Information commissioned Kleijnen Systematic Reviews Ltd to consult and perform tasks to enhance the PRISMA compliance and rigour of a systematic review on Conceptual Approaches and Operationalizations of

Trajmesa: A distributed nosql storage engine for big trajectory data
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Trajectory data is very useful for many urban applications. However, due to its spatio- temporal and high-volume properties, it is challenging to manage trajectory data . Existing trajectory data management frameworks suffer from scalability problem, and only support

How big data might induce learning with interactive visualization tools
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The essay presents some results of an initial collaboration carried out between Polytechnic of Turin and CSI Piemonte (In-house ICT company of Piemonte Region). Different data visualization tools were selected and studied (Gapminder, ManyEyes, Open eXplorer and

CONCURRENT ENGINEERING AND SEARCH BASED APPLICATIONS FOR 3D BIG DATA
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The imminent development of all European companies competitiveness will be firmly connected to their capacity to conceive innovative products. In the last years, clients demand started to be higher and more complex. Because of that, managing products development

Quality and Security in Big Data : Challenges as opportunities to build a powerful wrap-up solution
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Quality and Security are two major issues in Big Data that pose many challenges. High volume, heterogeneity and high speed of data generation and processing are, amongst others, common challenges that must be addressed before setting up any data qualityI became aware of the importance of undertaking further research in the contractual analysis of databases during a masters course in European Intellectual Property Law at Stockholm University. One of the key aspects of the LL. M. course syllabus was a focus on copyrights

Labor market analysis and curriculum gap assessment using big data in Kenya
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Executive summary One of the biggest challenges in designing a labour market relevant curriculum is to make sure that the curriculum is up to date and uses the same vocabulary as the employers do. This has been relatively a little studied challenge: if we take almost any

PAGE Study: Summary of a study protocol to estimate the prevalence of severe asthma in Spain using big – data methods
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Asthma in Hospital Units in Spain (PAGE) study arises from the perspective of a widespread implementation of the electronic medical record and the scant data available on the prevalence of severe asthma in hospitals in our setting, the primary objective of which is to


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