Big Data Mining And Complexity

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Big Data In Complex And Social Networks

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Author : My T. Thai
language : en
Publisher: CRC Press
Release Date : 2016-12-01

Big Data In Complex And Social Networks written by My T. Thai and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-01 with Business & Economics categories.

This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

Big Data Mining And Complexity

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Author : Brian C. Castellani
language : en
Publisher: SAGE
Release Date : 2022-03-01

Big Data Mining And Complexity written by Brian C. Castellani and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Social Science categories.

This book offers a much needed critical introduction to data mining and ‘big data’. Supported by multiple case studies and examples, the authors provide: Digestible overviews of key terms and concepts relevant to using social media data in quantitative research. A critical review of data mining and ‘big data’ from a complexity science perspective, including its future potential and limitations A practical exploration of the challenges of putting together and managing a ‘big data’ database An evaluation of the core mathematical and conceptual frameworks, grounded in a case-based computational modeling perspective, which form the foundations of all data mining techniques Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.

Big Data In Complex Systems

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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2015-01-02

Big Data In Complex Systems written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-02 with Technology & Engineering categories.

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

Transparent Data Mining For Big And Small Data

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Author : Tania Cerquitelli
language : en
Publisher: Springer
Release Date : 2017-05-09

Transparent Data Mining For Big And Small Data written by Tania Cerquitelli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-09 with Computers categories.

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

Computational And Statistical Methods For Analysing Big Data With Applications

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Author : Shen Liu
language : en
Publisher: Academic Press
Release Date : 2015-11-20

Computational And Statistical Methods For Analysing Big Data With Applications written by Shen Liu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-20 with Mathematics categories.

Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. - Advanced computational and statistical methodologies for analysing big data are developed - Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable - Case studies are discussed to demonstrate the implementation of the developed methods - Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation - Computing code/programs are provided where appropriate

Principles Of Big Data

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Author : Jules J. Berman
language : en
Publisher: Newnes
Release Date : 2013-05-20

Principles Of Big Data written by Jules J. Berman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Computers categories.

Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. - Learn general methods for specifying Big Data in a way that is understandable to humans and to computers - Avoid the pitfalls in Big Data design and analysis - Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources

A Comprehensive Guide Through The Italian Database Research Over The Last 25 Years

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Author : Sergio Flesca
language : en
Publisher: Springer
Release Date : 2017-05-29

A Comprehensive Guide Through The Italian Database Research Over The Last 25 Years written by Sergio Flesca and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-29 with Technology & Engineering categories.

This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present—and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research. The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.

Digital Economy Complexity And Variety Vs Rationality

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Author : Elena G. Popkova
language : en
Publisher: Springer Nature
Release Date : 2019-09-14

Digital Economy Complexity And Variety Vs Rationality written by Elena G. Popkova and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-14 with Technology & Engineering categories.

This proceedings book features selected papers from the 9th National Scientific and Practical Conference “Digital Economy: Complexity and Variety Vs. Rationality,” which took place on April 17–18, 2019, in Vladimir (Russian Federation). It presents the latest research in the field of the digital economy, discussing its role in the creation of advantages for the state, entrepreneurship, and society, as well as the emergence of new economic risks. The chapters address the following topics: the importance of economy’s digital modernization, tools for the formation of the digital economy in Russia, specific features and perspectives of digital modernization of the regional economy, an overview of the social consequences of transition to the digital economy, financial components of the digital economy, legal challenges regarding the digital reality for society and state, and the main challenges and threats to the profession of jurisprudence in the context of the digitization of the economy. Intended for representatives of the academic community and researchers interested in the formation of the digital economy and digital society as well as undergraduates, postgraduates, and masters of economic specialties, the book is also a valuable resource for companies that use or wishing to implement digital technologies into their economic practices; and public and government employees involved with monitoring, control, and regulation of the digital economy.

Handbook On Cities And Complexity

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Author : Portugali, Juval
language : en
Publisher: Edward Elgar Publishing
Release Date : 2021-09-16

Handbook On Cities And Complexity written by Portugali, Juval and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-16 with Social Science categories.

Written by some of the founders of complexity theory and complexity theories of cities (CTC), this Handbook expertly guides the reader through over forty years of intertwined developments: the emergence of general theories of complex self-organized systems and the consequent emergence of CTC.

Big Data Technologies And Applications

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Author : Borko Furht
language : en
Publisher: Springer
Release Date : 2016-09-16

Big Data Technologies And Applications written by Borko Furht and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-16 with Computers categories.

The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.