This updated compendium provides the linear algebra background necessary to understand and develop linear algebra applications in data mining and machine learning.Basic knowledge and advanced new topics (spectral theory, singular values, decomposition techniques for matrices, tensors and multidimensional arrays) are presented together with several applications of linear algebra (k-means clustering, biplots, least square approximations, dimensionality reduction techniques, tensors and multidimensional arrays).The useful reference text includes more than 600 exercises and supplements, many with completed solutions and MATLAB applications.The volume benefits professionals, academics, researchers and graduate students in the fields of pattern recognition/image analysis, AI, machine learning and databases.

Everyone is already in the era of big data. It is gradually changing people's lifestyles. Therefore, it is necessary to explore the development path of big data, balance the relationship between technology, policy, and the market, so that it can better serve human society.This comprehensive book introduces what big data is, big data processing systems, big data management technologies, and big data analysis methods in an easy-to-understand language. It explains the specific applications of big data in smart government affairs, economic development, and the improvement of people's livelihood and welfare. The reference text also looks at the future development of big data.

The success of many companies through the assistance of bitcoin proves that technology continually dominates and transforms how economics operate. However, a deeper, more conceptual understanding of how these technologies work to identify innovation opportunities and how to successfully thrive in an increasingly competitive environment is needed for the entrepreneurs of tomorrow. Transforming Businesses With Bitcoin Mining and Blockchain Applications provides innovative insights into IT infrastructure and emerging trends in the realm of digital business technologies. This publication analyzes and extracts information from Bitcoin networks and provides the necessary steps to designing open blockchain. Highlighting topics that include financial markets, risk management, and smart technologies, the research contained within the title is ideal for entrepreneurs, business professionals, managers, executives, academicians, researchers, and business students.

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.

Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more.

The development of information technology in supply chains has shown that this digital revolution can be a source of performance for enterprises and governments. Among these technologies is blockchain. The application of blockchains in cryptocurrency reduces information security risks and eliminates several processing and transaction fees and allows countries with volatile currencies to have a more stable currency. Blockchain Applications in Cryptocurrency for Technological Evolution features a collection of contributions related to the application of blockchain technology in cryptocurrency. It further explains the ways in which these applications have affected the industry. Covering topics such as crypto mining attacks, data processing architecture, and purchase power, this premier reference source is an excellent resource for business leaders and executives, IT managers, logistics specialists, students and faculty of higher education, librarians, researchers, and academicians.

Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.

It is known that trust is of the utmost importance in human interactions, and blockchain technology establishes a new type of foundation for financial and political confidence. This new kind of trust is based on cryptographic techniques and distributed in digital networks. In an uncertain world where it is difficult to tell what is real or fake, decentralized organizational networks may prove to be particularly competitive given that this new ""distributed trust"" endows them with an unusual functional autonomy, namely guaranteeing the authenticity, confidentiality, and integrity of the processed data. Besides the direct sharing of information enabled by blockchain, transactions can now also take place with newfound trust and ways to safely manage personal data. It is important to look at these implications, particularly in sectors such as business and healthcare. Political and Economic Implications of Blockchain Technology in Business and Healthcare provides relevant theoretical frameworks on the political and economic impact of blockchain technology, which is thought to be able to redesign human interactions concerning transactions. Specifically, it will give ideas, concepts, and instruments considered relevant to advance the knowledge about ""cryptoeconomics"" and decentralized governance. The chapters will also provide several insights on business applications of this digital innovation, particularly in the healthcare sector, and will explore the ethical impact of the new ""distributed trust"" paradigm resulting from the surge of such a disruptive technology. This book is essential for students and researchers in social and life sciences, professionals and policymakers working in the fields of public and business administration, healthcare workers and researchers, academicians, and students interested in blockchain technology and the political and economic impacts in the industry.

The internet of things (IoT) is quickly growing into a large industry with a huge economic impact expected in the near future. However, the users' needs go beyond the existing web-like services, which do not provide satisfactory intelligence levels. Ambient intelligence services in IoT environments is an emerging research area that can change the way that technology and services are perceived by the users. Ambient Intelligence Services in IoT Environments: Emerging Research and Opportunities is a unique source that systemizes recent trends and advances for service development with such key technological enablers of modern ICT as ambient intelligence, IoT, web of things, and cyber-physical systems. The considered concepts and models are presented using a smart spaces approach with a particular focus on the Smart-M3 platform, which is now shaping into an open source technology for creating ontology-based smart spaces and is shifting towards the development of web of things applications and socio-cyber-physical systems. Containing coverage on a broad range of topics such as fog computing, smart environments, and virtual reality, multitudes of researchers, students, academicians, and professionals will benefit from this timely reference.

Information Security and Ethics: Social and Organizational Issues brings together examples of the latest research from a number of international scholars addressing a wide range of issues significant to this important and growing field of study. These issues are relevant to the wider society, as well as to the individual, citizen, educator, student and industry professional. With individual chapters focusing on areas including web accessibility; the digital divide; youth protection and surveillance; Information security; education; ethics in the Information professions and Internet voting; this book provides an invaluable resource for students, scholars and professionals currently working in information Technology related areas.

With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

Relational databases have been predominant for many years and are used throughout various industries. The current system faces challenges related to size and variety of data thus the NoSQL databases emerged. By joining these two database models, there is room for crucial developments in the field of computer science. Bridging Relational and NoSQL Databases is an innovative source of academic content on the convergence process between databases and describes key features of the next database generation. Featuring coverage on a wide variety of topics and perspectives such as BASE approach, CAP theorem, and hybrid and native solutions, this publication is ideally designed for professionals and researchers interested in the features and collaboration of relational and NoSQL databases.