This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an important reference for their current and future research and faculty will find the volume useful for assignments in presenting current approaches to unsupervised and semi-supervised learning in graduate-level seminar courses. The book is based on selected, expanded papers from the Fourth International Conference on Soft Computing in Data Science (2018). Includes new advances in clustering and classification using semi-supervised and unsupervised learning; Address new challenges arising in feature extraction and selection using semi-supervised and unsupervised learning; Features applications from healthcare, engineering, and text/social media mining that exploit techniques from semi-supervised and unsupervised learning.

With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.

Cloud technologies have revolutionized the way we store information and perform various computing tasks. With the rise of this new technology, the ability to secure information stored on the cloud becomes a concern. The Handbook of Research on Securing Cloud-Based Databases with Biometric Applications explores the latest innovations in promoting cloud security through human authentication techniques. Exploring methods of access by identification, including the analysis of facial features, fingerprints, DNA, dental characteristics, and voice patterns, this publication is designed especially for IT professionals, academicians, and upper-level students seeking current research surrounding cloud security.

More and more, the advance of enterprise computing and cloud technologies means that managers are responsible for retrieving data ad-hoc and constructing business reports for decision-making and storytelling. The technical competencies necessary for such tasks can be daunting, and most database teaching methods do little to mitigate the confusion. They tend to follow traditional computer science methods that expose all computational and matrix theory complexities as well as various design theories, and in so doing, they present an excess of information that unnecessarily complicates the learning process for business-minded readers. Zygiaris simplifies his teaching method in order to provide an accessible walkthrough of all technological advances of databases in the business environment. Readers learn how to design, develop, and use databases to provide business analytical reports with the three major database management systems: Microsoft Access, Oracle Express and MariaDB (formerly MySQL). This is all delivered through clearly structured, streamlined chapters, all of which link to online videos that demonstrate visually, in step-by-step tutorials, how to implement the processes outlined in the book. All of these features help the non-IT student or manager to understand the importance of databases in the business environment and to learn how to use those databases to solve real-world problems. This book is of particular interest to students of management and to business managers, and it is of keen interest to anyone who works with major business database systems.

Today, more than 80% of the data transmitted over networks and archived on our computers, tablets, cell phones or clouds is multimedia data - images, videos, audio, 3D data. The applications of this data range from video games to healthcare, and include computer-aided design, video surveillance and biometrics. It is becoming increasingly urgent to secure this data, not only during transmission and archiving, but also during its retrieval and use. Indeed, in today's "all-digital" world, it is becoming ever-easier to copy data, view it unrightfully, steal it or falsify it. Multimedia Security 1 analyzes the issues of the authentication of multimedia data, code and the embedding of hidden data, both from the point of view of defense and attack. Regarding the embedding of hidden data, it also covers invisibility, color, tracing and 3D data, as well as the detection of hidden messages in an image by steganalysis.

Whether searching, shopping, or socializing, Web users leave behind a great deal of data revealing their information needs, mindset, and approaches used, creating vast opportunities for Web service providers as well as a host of security and privacy concerns for consumers. The Handbook of Research on Web Log Analysis reflects on the multifaceted themes of Web use and presents various approaches to log analysis. This expansive collection reviews the history of Web log analysis and examines new trends including the issues of privacy, social interaction and community building. Over XX research contributions from XX international experts comprehensively cover the latest user-behavior analytic and log analysis methodologies, and consider new research directions and novel applications. An essential holding for library reference collections, this Handbook of Research will benefit academics, researchers, and students in a variety of fields, as well as technology professionals interested in the opportunities and challenges presented by the massive collection of Web usage data.

As semantic technologies prove their value with targeted applications, there are increasing opportunities to consider their usefulness in social contexts for knowledge, learning, and human development. ""Social Web Evolution: Integrating Semantic Applications and Web 2.0 Technologies"" explores the potential of Web 2.0 and its synergies with the Semantic Web and provides state-of-the-art theoretical foundations and technological applications. A reference edition for academicians, practitioners, policy makers, and government officers eager for knowledge on Web 2.0 and social Web, this book emphasizes practical aspects of the integration of semantic applications into social Web technologies.

In the age of increasing reliance on data and the importance of sensitive information, applications and technologies have arisen to appropriately deal with assuring the security of medical informatics and healthcare administration functions. In order for technology to progress, new systems are being installed globally to address this issue. Governance of Picture Archiving and Communications Systems: Data Security and Quality Management of Filmless Radiology examines information security management systems for the facilitation of picture archiving and communication systems (PACS). This valuable contribution to data security and quality management literature provides a comprehensive guide for all aspects of the implementation of PACS for the enhancement of modern practices in radiology.

Collecting the latest research results from the leading researchers in the field of fuzzy object-oriented databases, Advances in Fuzzy Object-Oriented Databases: Modeling and Applications provide a single source for current research and practical applications in fuzzy object-oriented databases. This book includes major aspects of fuzzy object-oriented database modeling - conceptual, logical and physical, as well as details of implementations and applications. Readers will benefit from a complete understanding of the notions, techniques, and methods related to the research and developments of fuzzy object-oriented databases. This book can act as a starting point and a reference for their research and developments and stimulate the interest in the field of fuzzy object-oriented databases and further promote the research in the field.

In today's society, the utilization of social media platforms has become an abundant forum for individuals to post, share, tag, and, in some cases, overshare information about their daily lives. As significant amounts of data flood these venues, it has become necessary to find ways to collect and evaluate this information. Social Media Data Extraction and Content Analysis explores various social networking platforms and the technologies being utilized to gather and analyze information being posted to these venues. Highlighting emergent research, analytical techniques, and best practices in data extraction in global electronic culture, this publication is an essential reference source for researchers, academics, and professionals.

This book discusses various aspects of blockchains in economic systems and investment strategies in crypto markets. It first addresses the topic from a conceptual and theoretical point of view, and then analyzes it from an assessment and investment angle. Further, it examines the opportunities and limitations of the taxation of crypto currency, as well as the political implications, such as regulation of speculation with crypto currencies. The book is intended for academicians and students in the fields of economics and finance.

The growing presence of smart phones and smart devices has caused significant changes to wireless networks. With the ubiquity of these technologies, there is now increasingly more available data for mobile operators to utilize. Big Data Applications in the Telecommunications Industry is a comprehensive reference source for the latest scholarly material on the use of data analytics to study wireless networks and examines how these techniques can increase reliability and profitability, as well as network performance and connectivity. Featuring extensive coverage on relevant topics, such as accessibility, traffic data, and customer satisfaction, this publication is ideally designed for engineers, students, professionals, academics, and researchers seeking innovative perspectives on data science and wireless network communications. Topics Covered The many academic areas covered in this publication include, but are not limited to: Anomaly Detection Co-Occurrence Data Modeling Consumer Feedback Customer Satisfaction and Retention Network Accessibility Social Networks Traffic Data

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

This book conceptualises and develops crowdsourcing as an organisational business process. It argues that although for many organisations crowdsourcing still implies an immature one-off endeavour, when developed to a more repeatable business process it can harness innovation and agility. The book offers a process model to guide organisations towards the establishment of business process crowdsourcing (BPC), and empirically showcases and evaluates the model using two current major crowdsourcing projects. In order to consolidate the domain knowledge, the BPC model is turned into a heavyweight ontology capturing the concepts, hierarchical relationships and decision-making relationships necessary to establish crowdsourcing as a business process in an organisation. Lastly, based on the ontology it presents a decision tool that provides advice on making informed decisions about the performance of business process crowdsourcing activities.

In the mid-1970s, Whitfield Diffie and Martin Hellman invented public key cryptography, an innovation that ultimately changed the world. Today public key cryptography provides the primary basis for secure communication over the internet, enabling online work, socializing, shopping, government services, and much more. While other books have documented the development of public key cryptography, this is the first to provide a comprehensive insiders' perspective on the full impacts of public key cryptography, including six original chapters by nine distinguished scholars. The book begins with an original joint biography of the lives and careers of Diffie and Hellman, highlighting parallels and intersections, and contextualizing their work. Subsequent chapters show how public key cryptography helped establish an open cryptography community and made lasting impacts on computer and network security, theoretical computer science, mathematics, public policy, and society. The volume includes particularly influential articles by Diffie and Hellman, as well as newly transcribed interviews and Turing Award Lectures by both Diffie and Hellman. The contributed chapters provide new insights that are accessible to a wide range of readers, from computer science students and computer security professionals, to historians of technology and members of the general public. The chapters can be readily integrated into undergraduate and graduate courses on a range of topics, including computer security, theoretical computer science and mathematics, the history of computing, and science and technology policy.

Recent years have witnessed giant leaps in the strength of database technologies, creating a new level of capability to develop advanced applications that add value at unprecedented levels in all areas of information management and utilization. Parallel to this evolution is a need in the academia and industry for authoritative references to the research in this area, to establish a comprehensive knowledge base that will enable the information technology and managerial communities to realize maximum benefits from these innovations. Advanced Principles for Improving Database Design, Systems Modeling, and Software Development presents cutting-edge research and analysis of the most recent advancements in the fields of database systems and software development. This book provides academicians, researchers, and database practitioners with an exhaustive collection of studies that, together, represent the state of knowledge in the field.

This book illustrates all the concepts of web mining from gathering the web data sources to discovering and representing the extracted knowledge. This book is ideal for many researchers and scholars who are interested in a reference book that involves all the techniques and algorithms that are applied to a Web environment. This book illustrates, analyzes, and compares all the techniques, applications, and algorithms that are used in Web mining categories and provides a thorough overview to undergraduates, postgraduates, and scholars who wish to learn more about Web and data mining. The goal of this book is to foster transformative, multidisciplinary, and novel approaches that introduce the practical approach of analyzing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment. This book provides a complete overview of Web mining techniques and applications; it will be crucial for postgraduate students who want to understand the Web environment better and do not know the differences between Web mining and data mining. It will also be helpful for companies and organizations to discover practical solutions to handle their internet data in a more efficient way, as well as undergraduate students in software engineering and computer science engineering departments who do not have a complete reference book that offers them a full explanation about Web mining.

This book is an overview of current research in theoretical and practical aspects of security in distributed systems, in particular in information systems and related security tools. Issues treated in the book are security in XML-based management systems, security of multimedia data, technology and use of smart cards, applications of cryptography, security of distributed applications and adherence to standards, model and security issues associated with the organization of components (architectures) of information systems, such as networked systems (Internet and WWW-based), client/server architectures, andlayered architectures. Contributions come both from the academic and the industrial field.

This book contains a selection of papers presented during a special workshop on Complexity Science organized as part of the 9th International Conference on GIScience 2016. Expert researchers in the areas of Agent-Based Modeling, Complexity Theory, Network Theory, Big Data, and emerging methods of Analysis and Visualization for new types of data explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.

This contributed volume discusses diverse topics to demystify the rapidly emerging and evolving blockchain technology, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various business domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to this technology.

Recent advancements in technology have influenced major change within many industries. Because of such advancements, businesses and organizations are adapting to a more technology based work environment in order achieve a higher rate of production, output, and accuracy. Methodological Advancements in Intelligent Information Technologies: Evolutionary Trends brings together research from international authors detailing developments in intelligent information technologies and their impact on organizational environments. This esteemed reference publication covers topics on agent-based approaches to process management, semantic Web services, data mining techniques, engineering software technologies, and scalable and adaptive Web search engines, in order to provide current research for practitioners, educators, and students interested in the implementation of innovative technologies in a variety of work environments.

This book provides both a broad overview of the forecasting process, covering technological and human aspects alike, and deep insights into algorithms and platform functionalities in the IBP toolbox required to maximize forecast accuracy. Rich in technical and business explanations, it addresses short-, medium- and long-term forecasting processes using functionalities available in demand planning and demand sensing. There are also several theoretical concepts underpinning the algorithms discussed; these are explained with numerical examples to help demystify the IBP forecasting toolbox. Beyond standard procedures, the book also discusses custom approaches (e.g. new segmentation criteria, new outlier detection and correction methods) and new methods (e.g. the use of Markov chains for forecasting sporadic demands), etc. It subsequently benchmarks common practices using these innovative approaches and discusses the results. As measurement is an important precondition for improvement, an entire chapter is devoted to discussing process improvement and value using the Six Sigma methodology. In closing, the book provides several useful tips and tricks that should come in handy during project implementation.

This book presents a theory of information justice that subsumes the question of control and relates it to other issues that influence just social outcomes. Data does not exist by nature. Bureaucratic societies must provide standardized inputs for governing algorithms, a problem that can be understood as one of legibility. This requires, though, converting what we know about social objects and actions into data, narrowing the many possible representations of the objects to a definitive one using a series of translations. Information thus exists within a nexus of problems, data, models, and actions that the social actors constructing the data bring to it. This opens information to analysis from social and moral perspectives, while the scientistic view leaves us blind to the gains from such analysis-especially to the ways that embedded values and assumptions promote injustice. Toward Information Justice answers a key question for the 21st Century: how can an information-driven society be just? Many of those concerned with the ethics of data focus on control over data, and argue that if data is only controlled by the right people then just outcomes will emerge. There are serious problems with this control metaparadigm, however, especially related to the initial creation of data and prerequisites for its use. This text is suitable for academics in the fields of information ethics, political theory, philosophy of technology, and science and technology studies, as well as policy professionals who rely on data to reach increasingly problematic conclusions about courses of action.