Mathematics has been used as a tool in logistical reasoning for centuries. Examining how specific mathematic structures can aid in data and knowledge management helps determine how to efficiently and effectively process more information in these fields. N-ary Relations for Logical Analysis of Data and Knowledge is a critical scholarly reference source that provides a detailed study of the mathematical techniques currently involved in the progression of information technology fields. Featuring relevant topics that include algebraic sets, deductive analysis, defeasible reasoning, and probabilistic modeling, this publication is ideal for academicians, students, and researchers who are interested in staying apprised of the latest research in the information technology field.

The rise of intelligence and computation within technology has created an eruption of potential applications in numerous professional industries. Techniques such as data analysis, cloud computing, machine learning, and others have altered the traditional processes of various disciplines including healthcare, economics, transportation, and politics. Information technology in today’s world is beginning to uncover opportunities for experts in these fields that they are not yet aware of. The exposure of specific instances in which these devices are being implemented will assist other specialists in how to successfully utilize these transformative tools with the appropriate amount of discretion, safety, and awareness. Considering the level of diverse uses and practices throughout the globe, the fifth edition of the Encyclopedia of Information Science and Technology series continues the enduring legacy set forth by its predecessors as a premier reference that contributes the most cutting-edge concepts and methodologies to the research community. The Encyclopedia of Information Science and Technology, Fifth Edition is a three-volume set that includes 136 original and previously unpublished research chapters that present multidisciplinary research and expert insights into new methods and processes for understanding modern technological tools and their applications as well as emerging theories and ethical controversies surrounding the field of information science. Highlighting a wide range of topics such as natural language processing, decision support systems, and electronic government, this book offers strategies for implementing smart devices and analytics into various professional disciplines. The techniques discussed in this publication are ideal for IT professionals, developers, computer scientists, practitioners, managers, policymakers, engineers, data analysts, and programmers seeking to understand the latest developments within this field and who are looking to apply new tools and policies in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to software engineering, cybersecurity, information technology, media and communications, urban planning, computer science, healthcare, economics, environmental science, data management, and political science will benefit from the extensive knowledge compiled within this publication.

Those who want to understand logic, if they manage to pass at least an initial, though far from simple, modern course of study, eventually conclude that practically logic consists in formulating premises and a taken-from-nowhere assertion in an incomprehensible language and then proving or disproving cause-consequence links between them. Conversely, many topical tasks of logical analysis, such as forming and testing hypotheses, inferring consequences with predefined properties, and searching for, and analysis of, logical errors and inconsistencies in reasoning, among others, are outside the scope of this discourse. They are scattered haphazardly in works on theory of argumentation, non-classical logics, and artificial intelligence. This book demonstrates the capabilities of two relatively simple mathematical systems developed by the authors, namely E-structures and n-tuple algebra, which allow the modelling of various types of reasoning and solve the above and some other tasks of logical analysis.

The world is witnessing the growth of a global movement facilitated by technology and social media. Fueled by information, this movement contains enormous potential to create more accountable, efficient, responsive, and effective governments and businesses, as well as spurring economic growth. Big Data Governance and Perspectives in Knowledge Management is a collection of innovative research on the methods and applications of applying robust processes around data, and aligning organizations and skillsets around those processes. Highlighting a range of topics including data analytics, prediction analysis, and software development, this book is ideally designed for academicians, researchers, information science professionals, software developers, computer engineers, graduate-level computer science students, policymakers, and managers seeking current research on the convergence of big data and information governance as two major trends in information management.

Organizations are showing a remarkable interest in realizing knowledge management technologies and processes to adopt knowledge management as part of their overall strategy. However, even with the current advancement in technology, few organizations are entirely capable of developing critical organizational knowledge to achieve improved performance. Technological Innovations in Knowledge Management and Decision Support is a vital research publication that examines different knowledge management areas for organizational competitiveness, survival, and effectiveness. It also provides cutting-edge research techniques in related optimization methods and other automated techniques in real-world processes. Featuring a broad range of topics such as enterprise resource planning, neural networks, and image segmentation, this book is a critical resource for managers, IT specialists, healthcare and social sciences professionals, engineers, academicians, and researchers seeking research on effective knowledge management systems.

This book constitutes the proceedings of the 19th Russian Conference on Artificial Intelligence, RCAI 2021, held in Moscow, Russia, in October 2021. The 19 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 80 submissions. The conference deals with a wide range of topics, categorized into the following topical headings: cognitive research; data mining, machine learning, classification; knowledge engineering; multi-agent systems and robotics; natural language processing; fuzzy models and soft computer; intelligent systems; and tools for designing intelligent systems.

The modern world is developing at a pace where few can thoroughly keep track of its progress. More advancements in technology, evolving standards of education, and ongoing cultural and societal developments are leading to a need for improved pathways of knowledge discovery and dissemination. Knowledge-Intensive Economies and Opportunities for Social, Organizational, and Technological Growth provides emerging research exploring how academic research can represent both a bold response to the problems society faces today and a source of alternative solutions to those problems. This publication is derived from the basic understanding that education plays the role of the key enabler in the process of navigating these contemporary challenges. Featuring coverage on a broad range of topics such as e-service exploration, progressive online learning in urban areas, and advances in multimedia sharing, this book is ideally designed for consultants, academics, industry professionals, policymakers, politicians, and government officials seeking current research on the impact of information technology and the knowledge-based era.