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Digital Libraries: The Era of Big Data and Data Science

Digital Libraries: The Era of Big Data and Data Science PDF Author: Michelangelo Ceci
Publisher: Springer Nature
ISBN: 3030399052
Category : Computers
Languages : en
Pages : 197

Book Description
This book constitutes the thoroughly refereed proceedings of the 16th Italian Research Conference on Digital Libraries, IRCDL 2020, held in Bari, Italy, in January 2020. The 12 full papers and 6 short papers presented were carefully selected from 26 submissions. The papers are organized in topical sections on information retrieval, bid data and data science in DL; cultural heritage; open science.

Digital Libraries: The Era of Big Data and Data Science

Digital Libraries: The Era of Big Data and Data Science PDF Author: Michelangelo Ceci
Publisher: Springer Nature
ISBN: 3030399052
Category : Computers
Languages : en
Pages : 197

Book Description
This book constitutes the thoroughly refereed proceedings of the 16th Italian Research Conference on Digital Libraries, IRCDL 2020, held in Bari, Italy, in January 2020. The 12 full papers and 6 short papers presented were carefully selected from 26 submissions. The papers are organized in topical sections on information retrieval, bid data and data science in DL; cultural heritage; open science.

Encyclopedia of Data Science and Machine Learning

Encyclopedia of Data Science and Machine Learning PDF Author: Wang, John
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296

Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

R for Data Science

R for Data Science PDF Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521

Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Big Data

Big Data PDF Author: Viktor Mayer-Schönberger
Publisher: Houghton Mifflin Harcourt
ISBN: 0544002695
Category : Business & Economics
Languages : en
Pages : 257

Book Description
A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.

Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data

Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data PDF Author: Paul Zikopoulos
Publisher: McGraw Hill Professional
ISBN: 0071790543
Category : Computers
Languages : en
Pages : 176

Book Description
Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy PDF Author: John Macintyre
Publisher: Springer Nature
ISBN: 3030895114
Category : Computers
Languages : en
Pages : 999

Book Description
This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Internet Science

Internet Science PDF Author: Sotiris Diplaris
Publisher: Springer
ISBN: 3319775472
Category : Computers
Languages : en
Pages : 253

Book Description
This book constitutes the refereed post-conference proceedings of 4 workshops, held at the 4th International Conference on Internet Science, Thessaloniki, Greece, in November 2017: the Second International Workshop on the Internet for Financial Collective Awareness and Intelligence, IFIN 2017, the International Workshop on Data Economy 2017, the International Workshop on Digital Technology to Support Social Innovation, DSI 2017, and the International Workshop on Chatbot Research and Design, CONVERSATIONS 2017. The 17 full papers presented together with one short paper were carefully reviewed and selected from 27 submissions. The contributions of the IFIN workshop focus on a multidisciplinary dialogue on how to use the internet to promote financial awareness and capability among citizens whereas the papers of the Data Economy workshop show how online data change economy and business. The aim of the DSI workshop was to collect the lessons learned from different platforms and settings, and to understand the requirements and challenges for building and using digital platforms to effectively engage broad participation in the social innovation process. The papers of the Conversations workshop explore the brave new world of human-computer communication through natural language, gathering latest developments in chatbots research and design.

Big Data Analytics with SAS

Big Data Analytics with SAS PDF Author: David Pope
Publisher: Packt Publishing Ltd
ISBN: 1788294319
Category : Computers
Languages : en
Pages : 258

Book Description
Leverage the capabilities of SAS to process and analyze Big Data About This Book Combine SAS with platforms such as Hadoop, SAP HANA, and Cloud Foundry-based platforms for effecient Big Data analytics Learn how to use the web browser-based SAS Studio and iPython Jupyter Notebook interfaces with SAS Practical, real-world examples on predictive modeling, forecasting, optimizing and reporting your Big Data analysis with SAS Who This Book Is For SAS professionals and data analysts who wish to perform analytics on Big Data using SAS to gain actionable insights will find this book to be very useful. If you are a data science professional looking to perform large-scale analytics with SAS, this book will also help you. A basic understanding of SAS will be helpful, but is not mandatory. What You Will Learn Configure a free version of SAS in order do hands-on exercises dealing with data management, analysis, and reporting. Understand the basic concepts of the SAS language which consists of the data step (for data preparation) and procedures (or PROCs) for analysis. Make use of the web browser based SAS Studio and iPython Jupyter Notebook interfaces for coding in the SAS, DS2, and FedSQL programming languages. Understand how the DS2 programming language plays an important role in Big Data preparation and analysis using SAS Integrate and work efficiently with Big Data platforms like Hadoop, SAP HANA, and cloud foundry based systems. In Detail SAS has been recognized by Money Magazine and Payscale as one of the top business skills to learn in order to advance one's career. Through innovative data management, analytics, and business intelligence software and services, SAS helps customers solve their business problems by allowing them to make better decisions faster. This book introduces the reader to the SAS and how they can use SAS to perform efficient analysis on any size data, including Big Data. The reader will learn how to prepare data for analysis, perform predictive, forecasting, and optimization analysis and then deploy or report on the results of these analyses. While performing the coding examples within this book the reader will learn how to use the web browser based SAS Studio and iPython Jupyter Notebook interfaces for working with SAS. Finally, the reader will learn how SAS's architecture is engineered and designed to scale up and/or out and be combined with the open source offerings such as Hadoop, Python, and R. By the end of this book, you will be able to clearly understand how you can efficiently analyze Big Data using SAS. Style and approach The book starts off by introducing the reader to SAS and the SAS programming language which provides data management, analytical, and reporting capabilities. Most chapters include hands on examples which highlights how SAS provides The Power to Know©. The reader will learn that if they are looking to perform large-scale data analysis that SAS provides an open platform engineered and designed to scale both up and out which allows the power of SAS to combine with open source offerings such as Hadoop, Python, and R.

Big Data Analytics for Cyber-Physical System in Smart City

Big Data Analytics for Cyber-Physical System in Smart City PDF Author: Mohammed Atiquzzaman
Publisher: Springer Nature
ISBN: 9813345721
Category : Technology & Engineering
Languages : en
Pages : 1868

Book Description
This book gathers a selection of peer-reviewed papers presented at the second Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020) conference, held in Shanghai, China, on 28–29 December 2020. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Research Anthology on Collaboration, Digital Services, and Resource Management for the Sustainability of Libraries

Research Anthology on Collaboration, Digital Services, and Resource Management for the Sustainability of Libraries PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799881059
Category : Language Arts & Disciplines
Languages : en
Pages : 1096

Book Description
Faced with increased budget cuts, libraries must continue to advance their services through new technologies and practices in order to keep pace with the rapid changes society is currently facing. The once traditional in-person services offered can no longer be the only option, and to keep themselves afloat, libraries must offer more in terms of digital services. The convenience of offering mobile and digital services brings a new wave of accessibility to libraries and a new question on just how much libraries will need to change to meet the newfound needs of its patrons. Beyond offering these digital services, libraries are incorporating other types of technology in multifaceted ways such as utilizing artificial intelligence practices, social media, and big data management. Moreover, libraries are increasingly looking for ways to partner and collaborate with the community, faculty, students, and other libraries in order to keep abreast of the best practices and needs of their users. The Research Anthology on Collaboration, Digital Services, and Resource Management for the Sustainability of Libraries explores emerging strategies and technologies that are redefining the role of the library within communities and academia. This reference book covers extensive ground on all the ways libraries have shifted to manage their resources, digitalize their services, and market themselves within the new technological revolution. These continued shifts for libraries come with benefits, challenges, and future projections that are critical for discussion as libraries continue to strive to remain updated and relevant in times of change. This book is ideal for librarians, archivists, collection managers, IT specialists, electronic resource librarians, practitioners, stakeholders, researchers, academicians, and students who are interested in the current state of libraries and how they are transforming to fit modern needs.