This book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation, and anthropic-oriented computing that were originally presented at the 15th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2021), being held as a Virtual Conference in June 14-16, 2021. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems, and nature-inspired manufacturing, all of which contribute to the modern digital economy.

This book provides an overview of fake news detection, both through a variety of tutorial-style survey articles that capture advancements in the field from various facets and in a somewhat unique direction through expert perspectives from various disciplines. The approach is based on the idea that advancing the frontier on data science approaches for fake news is an interdisciplinary effort, and that perspectives from domain experts are crucial to shape the next generation of methods and tools. The fake news challenge cuts across a number of data science subfields such as graph analytics, mining of spatio-temporal data, information retrieval, natural language processing, computer vision and image processing, to name a few. This book will present a number of tutorial-style surveys that summarize a range of recent work in the field. In a unique feature, this book includes perspective notes from experts in disciplines such as linguistics, anthropology, medicine and politics that will help to shape the next generation of data science research in fake news. The main target groups of this book are academic and industrial researchers working in the area of data science, and with interests in devising and applying data science technologies for fake news detection. For young researchers such as PhD students, a review of data science work on fake news is provided, equipping them with enough know-how to start engaging in research within the area. For experienced researchers, the detailed descriptions of approaches will enable them to take seasoned choices in identifying promising directions for future research.

This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2021), held at Hanoi in Vietnam. It includes peer-reviewed high-quality articles on intelligent system and networks. It brings together professionals and researchers in the area and presents a platform for exchange of ideas and to foster future collaboration. The topics covered in this book include-foundations of computer science; computational intelligence language and speech processing; software engineering software development methods; wireless communications signal processing for communications; electronics track IoT and sensor systems embedded systems; etc.

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.

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.

This book discusses the various open issues of blockchain technology, such as the efficiency of blockchain in different domains of digital cryptocurrency, smart contracts, smart education system, smart cities, cloud identity and access, safeguard to cybersecurity and health care. For the first time in human history, people across the world can trust each other and transact over a large peer-to-peer networks without any central authority. This proves that, trust can be built not only by centralized institution but also by protocols and cryptographic mechanisms. The potential and collaboration between organizations and individuals within peer networks make it possible to potentially move to a global collaborative network without centralization. Blockchain is a complex social, economic and technological phenomenon. This questions what the established terminologies of the modern world like currency, trust, economics and exchange would mean. To make any sense, one needs to realize how much insightful and potential it is in the context and the way it is technically developed. Due to rapid changes in accessing the documents through online transactions and transferring the currency online, many previously used methods are proving insufficient and not secure to solve the problem which arises in the safe and hassle-free transaction. Nowadays, the world changes rapidly, and a transition flow is also seen in Business Process Management (BPM). The traditional Business Process Management holds good establishment last one to two decades, but, the internal workflow confined in a single organization. They do not manage the workflow process and information across organizations. If they do so, again fall in the same trap as the control transfers to the third party that is centralized server and it leads to tampering the data, and single point of failure. To address these issues, this book highlights a number of unique problems and effective solutions that reflects the state-of-the art in blockchain Technology. This book explores new experiments and yields promising solutions to the current challenges of blockchain technology. This book is intended for the researchers, academicians, faculties, scientists, blockchain specialists, business management and software industry professionals who will find it beneficial for their research work and set new ideas in the field of blockchain. This book caters research work in many fields of blockchain engineering, and it provides an in-depth knowledge of the fields covered.

This book provides practical information about web archives, offers inspiring examples for web archivists, raises new challenges, and shares recent research results about access methods to explore information from the past preserved by web archives. The book is structured in six parts. Part 1 advocates for the importance of web archives to preserve our collective memory in the digital era, demonstrates the problem of web ephemera and shows how web archiving activities have been trying to address this challenge. Part 2 then focuses on different strategies for selecting web content to be preserved and on the media types that different web archives host. It provides an overview of efforts to address the preservation of web content as well as smaller-scale but high-quality collections of social media or audiovisual content. Next, Part 3 presents examples of initiatives to improve access to archived web information and provides an overview of access mechanisms for web archives designed to be used by humans or automatically accessed by machines. Part 4 presents research use cases for web archives. It also discusses how to engage more researchers in exploiting web archives and provides inspiring research studies performed using the exploration of web archives. Subsequently, Part 5 demonstrates that web archives should become crucial infrastructures for modern connected societies. It makes the case for developing web archives as research infrastructures and presents several inspiring examples of added-value services built on web archives. Lastly, Part 6 reflects on the evolution of the web and the sustainability of web archiving activities. It debates the requirements and challenges for web archives if they are to assume the responsibility of being societal infrastructures that enable the preservation of memory. This book targets academics and advanced professionals in a broad range of research areas such as digital humanities, social sciences, history, media studies and information or computer science. It also aims to fill the need for a scholarly overview to support lecturers who would like to introduce web archiving into their courses by offering an initial reference for students.

This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors' intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors' attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits * Presents the latest advances in learning automata-based optimization approaches. * Addresses the memetic models of learning automata for solving NP-hard problems. * Discusses the application of learning automata for behavior control in evolutionary computation in detail. * Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

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.

This is a rigorous and complete textbook for a first course on information retrieval from the computer science perspective. It provides an up-to-date student oriented treatment of information retrieval including extensive coverage of new topics such as web retrieval, web crawling, open source search engines and user interfaces.

From parsing to indexing, clustering to classification, retrieval to ranking, and user feedback to retrieval evaluation, all of the most important concepts are carefully introduced and exemplified. The contents and structure of the book have been carefully designed by the two main authors, with individual contributions coming from leading international authorities in the field, including Yoelle Maarek, Senior Director of Yahoo Research Israel; Dulce Ponceleon IBM Research; and Malcolm Slaney, Yahoo Research USA.

This completely reorganized, revised and enlarged second edition of "Modern Information Retrieval" contains many new chapters and double the number of pages and bibliographic references of the first edition, and a companion website www.mir2ed.org with teaching material. It will prove invaluable to students, professors, researchers, practitioners, and scholars of this fascinating field of information retrieval.

In The Political Economy and Feasibility of Bitcoin and Cryptocurrencies Spencer J. Pack brings his authority as a scholar and advisor to this study of bitcoin and cryptocurrencies from the perspective of the history of economic thought. Major theorists analyzed in depth include Aristotle, Smith, Law, Marx, Keynes, Rothbard and Hayek, and the book draws extensively upon the ideas of Schumpeter, Galbraith and Sraffa. The book argues for reconceptualization of the basic microeconomic categories into rental, sale and financial asset prices along with a reconsideration of Keynes' general theory to his special theory and Rothbard's relationship to Rousseau. The author posits that intense theoretical and practical struggles will continue over who should control the quantity of money, the cause of the capitalist economy's instability, and who or what is more dangerous: concentrated centers of private wealth and private enterprises or the contemporary state. He concludes that in terms of the quality of money, the cryptocurrency community is probably correct, with new forms of money potentially being better than sovereign fiat currency. The book's relevance will appeal to members of the history of economic thought community, economic theorists, and political science and political theory scholars as well as to policy makers and members of the cryptocurrency community.

This book focuses on the combination of IoT and data science, in particular how methods, algorithms, and tools from data science can effectively support IoT. The authors show how data science methodologies, techniques and tools, can translate data into information, enabling the effectiveness and usefulness of new services offered by IoT stakeholders. The authors posit that if IoT is indeed the infrastructure of the future, data structure is the key that can lead to a significant improvement of human life. The book aims to present innovative IoT applications as well as ongoing research that exploit modern data science approaches. Readers are offered issues and challenges in a cross-disciplinary scenario that involves both IoT and data science fields. The book features contributions from academics, researchers, and professionals from both fields.

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.

This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns. With good data being key to staying ahead in a competitive market, enterprises capture and store exponential volumes of data. Considering the business impact of data, there needs to be adequate management around it to derive the best value. Data governance is one of the core data management related functions. However, it is often overlooked, misunderstood or confused with other terminologies and data management functions. Given the pervasiveness of data and the importance of data, this book provides comprehensive understanding of the business drivers for data governance and benefits of data governance, the interactions of data governance function with other data management functions and various components and aspects of data governance that can be facilitated by technology and tools, the distinction between data management tools and data governance tools, the readiness checks to perform before exploring the market to purchase a data governance tool, the different aspects that must be considered when comparing and selecting the appropriate data governance technologies and tools from large number of options available in the marketplace and the different market players that provide tools for supporting data governance. This book combines the data and data governance knowledge that the author has gained over years of working in different industrial and research programs and projects associated with data, processes and technologies with unique perspectives gained through interviews with thought leaders and data experts. This book is highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge and get guidance on implementing data governance in their own data initiatives.

This book offers ideas to help improve digital technologies and increase their efficiency during implementation and application for researchers and practitioners. The outstanding position of the book among others is that it dwells with cyber-physical systems' progress and proposes ideas and finding around digital tools and technologies and their application. A distinguished contribution is in presenting results on Digital Twins development and application, enhancing approaches of communication and information transferring between cyber-physical systems connected within the Internet of things platforms, computer linguistic as a part of cyber-physical systems, intelligent cybersecurity and computer vision systems. The target audience of this book also includes practitioners and experts, as well as state authorities and representatives of manufacturing and industry who are interested in creating and implementing of cyber-physical systems in framework of digitalization projects.

This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy.

This book features selected papers presented at the 3rd International Conference on Recent Innovations in Computing (ICRIC 2020), held on 20-21 March 2020 at the Central University of Jammu, India, and organized by the university's Department of Computer Science & Information Technology. It includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.

This book constitutes the refereed post-conference proceedings of the First IFIP TC 5 International Conference on Computer Science Protecting Human Society Against Epidemics, ANTICOVID 2021, held virtually in June 2021.The 7 full and 4 short papers presented were carefully reviewed and selected from 20 submissions. The papers are concerned with a very large spectrum of problems, ranging from linguistics for automatic translation of medical terms, to a proposition for a worldwide system of fast reaction to emerging pandemic.