This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.

To optimally design and manage a directory service, IS architects and managers must understand current state-of-the-art products. Directory Services covers Novell's NDS eDirectory, Microsoft's Active Directory, UNIX directories and products by NEXOR, MaxWare, Siemens, Critical Path and others. Directory design fundamentals and products are woven into case studies of large enterprise deployments. Cox thoroughly explores replication, security, migration and legacy system integration and interoperability. Business issues such as how to cost justify, plan, budget and manage a directory project are also included. The book culminates in a visionary discussion of future trends and emerging directory technologies including the strategic direction of the top directory products, the impact of wireless technology on directory enabled applications and using directories to customize content delivery from the Enterprise Portal.
Directory Services is a comprehensive and practical guide that provides organizations and consultants with a roadmap used to create the directory enabled global enterprise. To provide the reader with the core knowledge required for designing directory services, the book discusses directory fundamentals including X.500, X.509 and LDAP as well as how to cost justify, plan, budget and manage a directory project
Provides critical info for design, integration, or migration for multiple messaging platforms
Covers all major directories
Provides case studies and guidelines for deployment and integration issues

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.

Recent research reveals that socioeconomic factors of the neighborhoods where road users live and where pedestrian-vehicle crashes occur are important in determining the severity of the crashes, with the former having a greater influence. Hence, road safety countermeasures, especially those focusing on the road users, should be targeted at these high risk neighborhoods. Big Data Analytics in Traffic and Transportation Engineering: Emerging Research and Opportunities is an essential reference source that discusses access to transportation and examines vehicle-pedestrian crashes, specifically in relation to socioeconomic factors that influence them, main predictors, factors that contribute to crash severity, and the enhancement of pedestrian safety measures. Featuring research on topics such as public transport, accessibility, and spatial distribution, this book is ideally designed for policymakers, transportation engineers, road safety designers, transport planners and managers, professionals, academicians, researchers, and public administrators.

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.

The explosion of computer use and internet communication has placed new emphasis on the ability to store, retrieve and search for all types of images, both still photo and video images. The success and the future of visual information retrieval depends on the cutting edge research and applications explored in this book. It combines the expertise from both computer vision and database research.
Unlike text retrieval and text/numeric databases the challenges of image databases are enormous. How do you use "data mining" to search for an image if you do not have "key words" to search? Exploratory Image Databases introduces the idea that it is possible to solve this problem by merging database systems into a single search and browse activity called "exploration."
Exploratory Image Databases is one of the first single-author books that unifies the critical emerging topic of image databases. A new approach to image databases, the work is divided into four central parts: introduction to the problems that image database research must solve; computer vision and information retrieval techniques; image database issues; and interface and engines for visual searches.
Example: Imagine the difficulty of building and using a database for "face recognition," where an image of a face is used. In order to effectively use the image a huge number of characteristics would need to be entered in the database. The goal of future image databases is to use hardware and software to recognize and categorize images without typing in characteristics.
* Comprehensive coverage of the image analysis as well as the database/theoretical aspects of image databases.
* Extensive coverage of interfaces and interaction models, with a theoretical framework for the development of new interaction schemes.
* Identifies three interaction models between users and image databases, two of which have no counterpart in traditional databases.
* Coverage of the relation between image and text, including mixed search models and the automatic determination of the relation between images and text on large corpuses like the web.
* Analysis of the process of signification in images and its influence on the interaction models and technological problems of image databases.

Spatial Databases: Technologies, Techniques and Trends Introduces the reader to the world of spatial databases, and related subtopics. The broad range of topics covered within the chapters includes spatial data modeling, indexing of spatial and spatiotemporal objects, data mining and knowledge discovery in spatial and spatiotemporal management issues and query processing for moving objects. The reader will be able to get in touch with several important research issues the research community is dealing with today. Covering fundamental aspects up to advanced material, this book appeals to a broad computer science audience. Although perfect for specialists, each chapter is self-contained, making it easy for non-specialists to grasp the main issues involved.

The increasing trend of multimedia data use is likely to accelerate creating an urgent need of providing a clear means of capturing, storing, indexing, retrieving, analyzing, and summarizing data through image data. ""Artificial Intelligence for Maximizing Content Based Image Retrieval"" discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field. Providing state-of-the-art research from leading international experts, this book offers a theoretical perspective and practical solutions for academicians, researchers, and industry practitioners.

Here's a thorough introduction to the latest developments in database systems design presented from an applications point of view. Featuring contributions from well-known experts in the field, this book pays special attention to issues raised by new trends in database design, and how these developments affect the programmer and database administrator.

Intelligent methods are used in distributed environments in countless ways, with examples such as propagation, communication, collaboration, and cooperation. With the abundant purposes for intelligence in distributed systems, it is pertinent for researchers, technicians, and students in various areas of computer science to discover the most current and definitive advances in the field.""Intelligence Integration in Distributed Knowledge Management"" provides recent technologies and practices in intelligence for distributed systems, while covering major aspects of the agent based systems. This book is a must for those striving to enhance their understanding of distributed knowledge management and extend their ideas of cooperation using for numerous real-world problems.

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.

"Component Database Systems" is a collection of invited chapters by the researchers making the most influential contributions in the database industry's trend toward componentization

This book represents the sometimes-divergent, sometimes-convergent approaches taken by leading database vendors as they seek to establish commercially viable componentization strategies. Together, these contributions form the first book devoted entirely to the technical and architectural design of component-based database systems. In addition to detailing the current state of their research, the authors also take up many of the issues affecting the likely future directions of component databases.

If you have a stake in the evolution of any of today's leading database systems, this book will make fascinating reading. It will also help prepare you for the technology that is likely to become widely available over the next several years.
* Is comprised of contributions from the field's most highly respected researchers, including key figures at IBM, Oracle, Informix, Microsoft, and POET.
* Represents the entire spectrum of approaches taken by leading software companies working on DBMS componentization strategies.
* Covers component-focused architectures, methods for hooking components into an overall system, and support for component development.
* Examines the component technologies that are most valuable to Web-based and multimedia databases.
* Presents a thorough classification and overview of component database systems.

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.

As the world has entered the era of big data, there is a need to give a semantic perspective to the data to find unseen patterns, derive meaningful information, and make intelligent decisions. This 2-volume handbook set is a unique, comprehensive, and complete presentation of the current progress and future potential explorations in the field of data science and related topics. Handbook of Data Science with Semantic Technologies provides a roadmap for a new trend and future development of data science with semantic technologies. The first volume serves as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for both academic researchers and industry professionals. The second volume provides a roadmap for the deployment of semantic technologies in the field of data science that enables users to create intelligence through these technologies by exploring the opportunities while eradicating the current and future challenges. The set explores the optimal use of these technologies to provide the maximum benefit to the user under one comprehensive source. This set consisting of two separate volumes can be utilized independently or together as an invaluable resource for students, scholars, researchers, professionals, and practitioners in the field.

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.

With almost every business application process being linked with a web portal, the website has become an integral part of any organization. Satisfying the end user's needs is one of the key principles of designing an effective website. Because there are different users for any given website, there are different criteria that users want. Thus, evaluating a website is a multi-criteria decision-making problem in which the decision maker's opinion should be considered for ranking the website. Multi-Criteria Decision-Making Models for Website Evaluation is a critical scholarly resource that covers the strategies needed to evaluate the navigability and efficacy of websites as promotional platforms for their companies. Featuring a wide range of topics including linguistic modelling, e-services, and site quality, this book is ideal for managers, executives, website designers, graphic artists, specialists, consultants, educationalists, researchers, and students.

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.

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.

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

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.