Classification Made Relevant: How Scientists Build and Use Classifications and Ontologies explains how classifications and ontologies are designed and used to analyze scientific information. The book presents the fundamentals of classification, leading up to a description of how computer scientists use object-oriented programming languages to model classifications and ontologies. Numerous examples are chosen from the Classification of Life, the Periodic Table of the Elements, and the symmetry relationships contained within the Classification Theorem of Finite Simple Groups. When these three classifications are tied together, they provide a relational hierarchy connecting all of the natural sciences. The book's chapters introduce and describe general concepts that can be understood by any intelligent reader. With each new concept, they follow practical examples selected from various scientific disciplines. In these cases, technical points and specialized vocabulary are linked to glossary items where the item is clarified and expanded.

Data mining analysis techniques have undergone significant developments in recent years. This has led to improved uses throughout numerous functions and applications. Intelligent Multidimensional Data Clustering and Analysis is an authoritative reference source for the latest scholarly research on the advantages and challenges presented by the use of cluster analysis techniques. Highlighting theoretical foundations, computing paradigms, and real-world applications, this book is ideally designed for researchers, practitioners, upper-level students, and professionals interested in the latest developments in cluster analysis for large data sets.

Collaborative working has been increasingly viewed as a good practice for organizations to achieve efficiency. Organizations that work well in collaboration may have access to new sources of funding, deliver new, improved, and more integrated services, make savings on shared costs, and exchange knowledge, information and expertise. Collaboration and the Semantic Web: Social Networks, Knowledge Networks and Knowledge Resources showcases cutting-edge research on the intersections of Semantic Web, collaborative work, and social media research, exploring how the resources of so-called social networking applications, which bring people together to interact and encourage sharing of personal information and ideas, can be tapped by Semantic Web techniques, making shared Web contents readable and processable for machine and intelligent applications, as well as humans. Semantic technologies have shown their potential for integrating valuable knowledge, and they are being applied to the composition of digital learning and working platforms. Integrated semantic applications, linked data, social networks, and networked digital solutions can now be used in collaborative environments and present participants with the context-aware information that they need.

Technology has revolutionized the ways in which libraries store, share, and access information. As digital resources and tools continue to advance, so too do the opportunities for libraries to become more efficient and house more information. E-Discovery Tools and Applications in Modern Libraries presents critical research on the digitization of data and how this shift has impacted knowledge discovery, storage, and retrieval. This publication explores several emerging trends and concepts essential to electronic discovery, such as library portals, responsive websites, and federated search technology. The timely research presented within this publication is designed for use by librarians, graduate-level students, technology developers, and researchers in the field of library and information science.

Although some IoT systems are built for simple event control where a sensor signal triggers a corresponding reaction, many events are far more complex, requiring applications to interpret the event using analytical techniques to initiate proper actions. Artificial intelligence of things (AIoT) applies intelligence to the edge and gives devices the ability to understand the data, observe the environment around them, and decide what to do best with minimum human intervention. With the power of AI, AIoT devices are not just messengers feeding information to control centers. They have evolved into intelligent machines capable of performing self-driven analytics and acting independently. A smart environment uses technologies such as wearable devices, IoT, and mobile internet to dynamically access information, connect people, materials and institutions, and then actively manages and responds to the ecosystem's needs in an intelligent manner. In this edited book, the authors present challenges, technologies, applications and future trends of AI-enabled IoT (AIoT) in realizing smart and intelligent environments, including frameworks and methodologies to apply AIoT in monitoring devices and environments, tools and practices most applicable to product or service development to solve innovation problems, advanced and innovative techniques and practical implementations to enhance future smart environment systems as. They plan to cover a broad range of applications including smart cities, smart transportation and smart agriculture. This book is a valuable resource for industry and academic researchers, scientists, engineers and advanced students in the fields of ICTs and networking, IoT, AI and machine and deep learning, data science, sensing, robotics, automation and smart technologies and smart environments.

This book documents recent attempts to conduct systematic, prodigious and multidisciplinary research in learning analytics and present their findings and identify areas for further research and development. The book also unveils the distinguished and exemplary works by educators and researchers in the field highlighting the current trends, privacy and ethical issues, creative and unique approaches, innovative methods, frameworks, and theoretical and practical aspects of learning analytics.

The blockchain revolution has drastically impacted global economics and the strategic practices within different industries. Cryptocurrency specifically has forever changed the face of business and the implementation of business online. While innovative, people are still in the early stages of building and developing blockchain technology and its applications, and it is critical that researchers and practitioners obtain a better understanding of this global phenomenon. Architectures and Frameworks for Developing and Applying Blockchain Technology is an essential reference source that presents the technological foundation, recent research findings, developments, and critical issues associated with blockchain technology from both computer science and social science perspectives. Featuring topics such as artificial intelligence, digital economy, and network technology, this book is ideally designed for academics, researchers, industry leaders, IT consultants, engineers, programmers, practitioners, government officials, policymakers, and students.

Multimedia and its rich semantics are profligate in today s digital environment. Databases and content management systems serve as essential tools to ensure that the endless supply of multimedia content are indexed and remain accessible to end users. Methods and Innovations for Multimedia Database Content Management highlights original research on new theories, algorithms, technologies, system design, and implementation in multimedia data engineering and management with an emphasis on automatic indexing, tagging, high-order ranking, and rule mining. This book is an ideal resource for university researchers, scientists, industry professionals, software engineers and graduate students.

Privacy protection within large databases can be a challenge. By examining the current problems and challenges this domain is facing, more efficient strategies can be established to safeguard personal information against invasive pressures. HCI Challenges and Privacy Preservation in Big Data Security is an informative scholarly publication that discusses how human-computer interaction impacts privacy and security in almost all sectors of modern life. Featuring relevant topics such as large scale security data, threat detection, big data encryption, and identity management, this reference source is ideal for academicians, researchers, advanced-level students, and engineers that are interested in staying current on the advancements and drawbacks of human-computer interaction within the world of big data.

Technological advancements have led to many beneficial developments in the electronic world, especially in relation to online commerce. Unfortunately, these advancements have also created a prime hunting ground for hackers to obtain financially sensitive information and deterring these breaches in security has been difficult. Cryptographic Solutions for Secure Online Banking and Commerce discusses the challenges of providing security for online applications and transactions. Highlighting research on digital signatures, public key infrastructure, encryption algorithms, and digital certificates, as well as other e-commerce protocols, this book is an essential reference source for financial planners, academicians, researchers, advanced-level students, government officials, managers, and technology developers.

Managing Time in Relational Databases: How to Design, Update and Query Temporal Data introduces basic concepts that will enable businesses to develop their own framework for managing temporal data. It discusses the management of uni-temporal and bi-temporal data in relational databases, so that they can be seamlessly accessed together with current data; the encapsulation of temporal data structures and processes; ways to implement temporal data management as an enterprise solution; and the internalization of pipeline datasets. The book is organized into three parts. Part 1 traces the history of temporal data management and presents a taxonomy of bi-temporal data management methods. Part 2 provides an introduction to Asserted Versioning, covering the origins of Asserted Versioning; core concepts of Asserted Versioning; the schema common to all asserted version tables, as well as the various diagrams and notations used in the rest of the book; and how the basic scenario works when the target of that activity is an asserted version table. Part 3 deals with designing, maintaining, and querying asserted version databases. It discusses the design of Asserted Versioning databases; temporal transactions; deferred assertions and other pipeline datasets; Allen relationships; and optimizing Asserted Versioning databases.

In the literature of information science, a number of studies have been carried out attempting to model cognitive, affective, behavioral, and contextual factors associated with human information seeking and retrieval. On the other hand, only a few studies have addressed the exploration of creative thinking in music, focusing on understanding and describing individuals' information seeking behavior during the creative process. Trends in Music Information Seeking, Behavior, and Retrieval for Creativity connects theoretical concepts in information seeking and behavior to the music creative process. This publication presents new research, case studies, surveys, and theories related to various aspects of information retrieval and the information seeking behavior of diverse scholarly and professional music communities. Music professionals, theorists, researchers, and students will find this publication an essential resource for their professional and research needs.

Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent. The Handbook of Research on Advanced Research on Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.

The body of research in all aspects of Semantic Web development, design, and application continues to grow alongside new trends in the information systems community. Semantic-Enabled Advancements on the Web: Applications Across Industries reviews current and future trends in Semantic Web research with the aim of making existing and potential applications more accessible to a broader community of academics, practitioners, and industry professionals. Covering topics including recommendation systems, semantic search, and ontologies, this reference is a valuable contribution to the existing literature in this discipline.

Although an emerging technology, blockchain is here to stay. Since its inception, imaginative thinkers have identified new ways for this powerful technology to bring innovative solutions to problems in the business world. Considered by many as an extreme and disruptive change, how can business leaders overcome resistance to the implementation of blockchain solutions and maximize its potential? The Emerald Handbook of Blockchain for Business equips academics, practitioners, and students with a broad understanding of the cutting-edge developments and applications of emerging blockchain technology. Covering the basic concepts while also showcasing practical applications in intricate real-world situations, this handbook bridges the gap between theory and practice, providing a useful balance of detailed and user-friendly coverage. Facilitating readers with a working knowledge of how blockchain functions and integrates within the business world, this handbook is essential reading for academics looking for a springboard for further research and practitioners needing a go-to resource for navigating the implementation of this fast-moving new technology.

The long-standing debate on public vs. private healthcare systems has forced an examination of these organisations, in particular whether these approaches play corresponding or conflicting roles in service to global citizens. Healthcare Management and Economics: Perspectives on Public and Private Administration discusses public and private healthcare organisations by gathering perspectives on the differences in service, management, delivery, and efficiency. Highlighting the impact of citizens and information technology in these healthcare processes, this book is a vital collection of research for practitioners, academics, and scholars in the healthcare management field.

Education and research in the field of database technology can prove problematic without the proper resources and tools on the most relevant issues, trends, and advancements. Selected Readings on Database Technologies and Applications supplements course instruction and student research with quality chapters focused on key issues concerning the development, design, and analysis of databases. Containing over 30 chapters from authors across the globe, these selected readings in areas such as data warehousing, information retrieval, and knowledge discovery depict the most relevant and important areas of classroom discussion within the categories of Fundamental Concepts and Theories; Development and Design Methodologies; Tools and Technologies; Application and Utilization; Critical Issues; and Emerging Trends.

As data mining is one of the most rapidly changing disciplines with new technologies and concepts continually under development, academicians, researchers, and professionals of the discipline need access to the most current information about the concepts, issues, trends, and technologies in this emerging field.""Social Implications of Data Mining and Information Privacy: Interdisciplinary Frameworks and Solutions"" serves as a critical source of information related to emerging issues and solutions in data mining and the influence of political and socioeconomic factors. An immense breakthrough, this essential reference provides concise coverage of emerging issues and technological solutions in data mining, and covers problems with applicable laws governing such issues.

Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

New Methods of Market Research and Analysis prepares readers for the new reality posed by big data and marketing analytics. While connecting to traditional research approaches such as surveys and focus groups, this book shows how new technologies and new analytical capabilities are rapidly changing the way marketers obtain and process their information. In particular, the prevalence of big data systems always monitoring key performance indicators, trends toward more research using observation or observation and communication together, new technologies such as mobile, apps, geo-locators, and others, as well as the deep analytics allowed by cheap data processing and storage are all covered and placed in context. Scott Erickson goes beyond the buzzwords to provide relevant explanations of the meaning and impact of both big data and analytics, placing them in context with traditional marketing research. His engaging subject matter focuses on the practical aspects of big data concepts, precisely defining and illustrating key concepts and providing illuminating real world examples. This approachable style enables marketers to understand what data scientists are doing with big data systems and analytics, giving them a taste of the capabilities of contemporary statistical software and its practical applications. This book can be used as a supplement to a traditional marketing research text or on its own. It will serve as a key reference for graduate students and advanced undergraduates in marketing research, marketing analytics, or business intelligence courses as well as marketing professionals looking to stay up to date with current trends and have them explained in a context they understand.

Big data has presented a number of opportunities across industries. With these opportunities come a number of challenges associated with handling, analyzing, and storing large data sets. One solution to this challenge is cloud computing, which supports a massive storage and computation facility in order to accommodate big data processing. Managing and Processing Big Data in Cloud Computing explores the challenges of supporting big data processing and cloud-based platforms as a proposed solution. Emphasizing a number of crucial topics such as data analytics, wireless networks, mobile clouds, and machine learning, this publication meets the research needs of data analysts, IT professionals, researchers, graduate students, and educators in the areas of data science, computer programming, and IT development.