Mining goes Digital
Mining goes Digital

Author: Christoph Mueller

Publisher: CRC Press

Published: 2019-05-22

Total Pages: 759

ISBN-13: 1000398226

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The conferences on ‘Applications for Computers and Operations Research in the Minerals Industry’ (APCOM) initially focused on the optimization of geostatistics and resource estimation. Several standard methods used in these fields were presented in the early days of APCOM. While geostatistics remains an important part, information technology has emerged, and nowadays APCOM not only focuses on geostatistics and resource estimation, but has broadened its horizon to Information and Communication Technology (ICT) in the mineral industry. Mining Goes Digital is a collection of 90 high quality, peer reviewed papers covering recent ICT-related developments in: - Geostatistics and Resource Estimation - Mine Planning - Scheduling and Dispatch - Mine Safety and Mine Operation - Internet of Things, Robotics - Emerging Technologies - Synergies from other industries - General aspects of Digital Transformation in Mining Mining Goes Digital will be of interest to professionals and academics involved or interested in the above-mentioned areas.

Mining the Digital Information Networks
Mining the Digital Information Networks

Author: Niklas Lavesson

Publisher:

Published: 2013

Total Pages: 0

ISBN-13: 9781614992691

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Electronic publishing is continuously changing; new technologies open new ways for individuals, scholars, communities and networks to establish contacts, exchange data, produce information and share knowledge on a variety of devices, from personal computers to mobile media. There is an urgent need to rethink electronic publishing in order to develop and use new communication paradigms and technologies, and to devise a truly digital format for the future. This book presents the conference proceedings of the ELPUB 2013 conference, held in Karlskrona, Sweden, in June 2013. The main theme of the conference is extracting and processing data from the vast wealth of digital publishing, and the ways to use and reuse this information in innovative social contexts in a sustainable way. The conference brings together researchers and practitioners to discuss data mining, digital publishing and social networks, along with their implications for scholarly communication, information services, e-learning, e-businesses, the cultural heritage sector and other areas where electronic publishing is imperative. The book is divided into three sections: full research articles, full professional articles and extended abstracts. Each section is further subdivided into Data Mining and Intelligent Computing, Publishing and Access and Social Computing and Practices. Focusing on key issues surrounding the development of methods for gathering and processing information, and on the means for making these data useful and accessible, this book will be of interest to the whole digital community.

Industry 4.0
Industry 4.0

Author: Elena B. Zavyalova

Publisher: Springer Nature

Published: 2021-08-09

Total Pages: 450

ISBN-13: 3030754057

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This book reflects the futuristic scientific view of the consequences of transition to Industry 4.0 for climate change. The authors present a systemic overview of the current negative consequences of digitization for the environment, new outlines of the energy sphere in Industry 4.0 and the change of the environment pollution level in Industry 4.0. The book also analyses the ecological consequences of growth and development of Industry 4.0, and considers Industry 4.0 as an alternative to fighting climate change. The book presents a view on fighting climate change in Industry 4.0 from the positions of shifting the global community’s attention from environment protection to formation of the digital economy. A logical continuation of this book is a view from the opposite side, which would allow reflecting the contribution of Industry 4.0 into fighting climate change and the perspectives of harmonization of these top-priority directions of the global economy’s development. This book will be of interest to academics and practitioners interested in climate change and development of Industry 4.0, as well contributing to a national economic policy for fighting climate change and corporate strategies of sustainable development in Industry 4.0.

Process Mining in Action
Process Mining in Action

Author: Lars Reinkemeyer

Publisher: Springer Nature

Published: 2020-03-14

Total Pages: 216

ISBN-13: 3030401723

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This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment. The book is divided into three parts: Part I provides an introduction to the topic from fundamental principles to key success factors, and an overview of operational use cases. As a holistic description of process mining in a business environment, this part is particularly useful for readers not yet familiar with the topic. Part II presents detailed use cases written by contributors from a variety of functions and industries. Lastly, Part III provides a brief overview of the future of process mining, both from academic and operational perspectives. Based on a solid academic foundation, process mining has received increasing interest from operational businesses, with many companies already reaping the benefits. As the first book to present an overview of successful industrial applications, it is of particular interest to professionals who want to learn more about the possibilities and opportunities this new technology offers. It is also a valuable resource for researchers looking for empirical results when considering requirements for enhancements and further developments.

Data Preparation for Data Mining
Data Preparation for Data Mining

Author: Dorian Pyle

Publisher: Morgan Kaufmann

Published: 1999-03-22

Total Pages: 566

ISBN-13: 9781558605299

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This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance.

Principles of Data Mining
Principles of Data Mining

Author: Max Bramer

Publisher: Springer

Published: 2016-11-09

Total Pages: 530

ISBN-13: 1447173074

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This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.

Beyond Digital
Beyond Digital

Author: Paul Leinwand

Publisher: Harvard Business Press

Published: 2022-01-04

Total Pages: 142

ISBN-13: 1647822335

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Two world-renowned strategists detail the seven leadership imperatives for transforming companies in the new digital era. Digital transformation is critical. But winning in today's world requires more than digitization. It requires understanding that the nature of competitive advantage has shifted—and that being digital is not enough. In Beyond Digital, Paul Leinwand and Matt Mani from Strategy&, PwC's global strategy consulting business, take readers inside twelve companies and how they have navigated through this monumental shift: from Philips's reinvention from a broad conglomerate to a focused health technology player, to Cleveland Clinic's engagement with its broader ecosystem to improve and expand its leading patient care to more locations around the world, to Microsoft's overhaul of its global commercial business to drive customer outcomes. Other case studies include Adobe, Citigroup, Eli Lilly, Hitachi, Honeywell, Inditex, Komatsu, STC Pay, and Titan. Building on a major new body of research, the authors identify the seven imperatives that leaders must follow as the digital age continues to evolve: Reimagine your company's place in the world Embrace and create value via ecosystems Build a system of privileged insights with your customers Make your organization outcome-oriented Invert the focus of your leadership team Reinvent the social contract with your people Disrupt your own leadership approach Together, these seven imperatives comprise a playbook for how leaders can define a bolder purpose and transform their organizations.

Data Mining for the Masses, Third Edition
Data Mining for the Masses, Third Edition

Author: Matthew North

Publisher:

Published: 2018-09-05

Total Pages: 310

ISBN-13: 9781727102475

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Some say we live in the Information Age; others, the Social Age; and still others, the Big Data Age. Regardless of what name we give it, we live in an age that generates monumental amounts of data-in all different kinds of formats. In business, and in our personal lives, we use smartphones and tablets, web sites and watches; with apps and interfaces to shop, learn, entertain and inform. Businesses increasingly use technology to interact with consumers to provide marketing, customer service, product information and more. All of this technological activity generates data, and we're increasingly good at gathering, storing and analyzing it.Data mining can help to identify interesting patterns and messages that exist in data, often hidden beneath the surface. In this modern age of information systems, it is easier than ever before to extract meaning from data. From classification to prediction, data mining can help.In Data Mining for the Masses, Third Edition, professor Matt North-a former risk analyst and software engineer at eBay-uses simple examples and clear explanations with free, powerful software tools to teach you the basics of data mining. In this Third Edition, implementations of these examples are offered in current versions of the RapidMiner software, and in the increasingly popular R Statistical Package.You've got more data than ever before and you know it's got value, if only you can figure out how to get to it. This book can show you how. Let's start digging!

Mining Social Media
Mining Social Media

Author: Lam Thuy Vo

Publisher: No Starch Press

Published: 2019-11-25

Total Pages: 210

ISBN-13: 1593279167

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BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web Download data archives and dig through them for insights Inspect HTML downloaded from websites for useful content Format, aggregate, sort, and filter your collected data using Google Sheets Create data visualizations to illustrate your discoveries Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.