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Books > Computing & IT > Applications of computing > Databases
There is a large increase in the amount of information available on World Wide Web and also in number of online databases. This information abundance increases the complexity of locating relevant information. Such a complexity drives the need for improved and intelligent systems for search and information retrieval. Intelligent Agents are currently used to improve the search and retrieval information on World Wide Web. The use of existing search and retrieval engines with the addition of intelligent agents allows a more comprehensive search with a performance that can be measured. Intelligent Agents for Mining and Information Retrieval discusses the foundation as well as the pratical side of intelligent agents and their theory and applications for web data mining and information retrieval. The book can used for researchers at the undergraduate and post-graduate levels as well as a reference of the state-of-art for cutting edge researchers.
Designed for managers struggling to understand the risks in organizations dependent on secure networks, this book applies economics not to generate breakthroughs in theoretical economics, but rather breakthroughs in understanding the problems of security.
This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.
Data Quality: The Accuracy Dimension is about assessing the quality
of corporate data and improving its accuracy using the data
profiling method. Corporate data is increasingly important as
companies continue to find new ways to use it. Likewise, improving
the accuracy of data in information systems is fast becoming a
major goal as companies realize how much it affects their bottom
line. Data profiling is a new technology that supports and enhances
the accuracy of databases throughout major IT shops. Jack Olson
explains data profiling and shows how it fits into the larger
picture of data quality.
The book gathers selected papers presented at the KES International Symposium on Smart Transportation Systems (KES-STS 2019). Modern transportation systems have undergone a rapid transformation in recent years. This has produced a range of vehicle technology innovations such as connected vehicles, self-driving cars, electric vehicles, Hyperloop, and even flying cars, and with them, fundamental changes in transport systems around the world. The book discusses current challenges, innovations and breakthroughs in Smart Transportation Systems, as well as transport infrastructure modeling, safety analysis, freeway operations, intersection analysis, and other related cutting-edge topics.
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.
In this third edition of Vehicle Accident Analysis & Reconstruction Methods, Raymond M. Brach and R. Matthew Brach have expanded and updated their essential work for professionals in the field of accident reconstruction. Most accidents can be reconstructed effectively using of calculations and investigative and experimental data: the authors present the latest scientific, engineering, and mathematical reconstruction methods, providing a firm scientific foundation for practitioners. Accidents that cannot be reconstructed using the methods in this book are rare. In recent decades, the field of crash reconstruction has been transformed through the use of technology. The advent of event data records (EDRs) on vehicles signaled the era of modern crash reconstruction, which utilizes the same physical evidence that was previously available as well as electronic data that are measured/captured before, during, and after the collision. There is increased demand for more professional and accurate reconstruction as more crash data is available from vehicle sensors. The third edition of this essential work includes a new chapter on the use of EDRs as well as examples using EDR data in accident reconstruction. Early chapters feature foundational material that is necessary for the understanding of vehicle collisions and vehicle motion; later chapters present applications of the methods and include example reconstructions. As a result, Vehicle Accident Analysis & Reconstruction Methods remains the definitive resource in accident reconstruction.
"This book is a boon to technology professionals who are
responsible for global integration projects. Faced with the
mind-boggling complexities of standardizing global data, global
processes and global e-commerce, even the most experienced
professionals are often at a loss. James Bean has created an
extraordinary compilation of standards information, and provided
his insight on how to resolve complex integration problems. This
book will benefit IT community at large, and I would encourage both
specialists and novices alike to bring this book into their
personal libraries." -- Arka Mukherjee, Ph.D., CEO, Global IDs Inc.
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.
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.
This book is the best way to make the leap from SQL-92 to SQL:
1999, but it is much more than just a simple bridge between the
two. The latest from celebrated SQL experts Jim Melton and Alan
Simon, "SQL: 1999" is a comprehensive, eminently practical account
of SQL's latest incarnation and a potent distillation of the
details required to put it to work. Written to accommodate both
novice and experienced SQL users, "SQL: 1999" focuses on the
language's capabilities, from the basic to the advanced, and the
way that real applications take advantage of them. Throughout, the
authors illustrate features and techniques with clear and often
entertaining references to their own custom database, which can be
downloaded from the companion Web site.
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.
Clustered configuration first hit the scene nearly 20 years ago
when Digital Equipment Corporation (DEC) introduced the VaxCluster.
Until now, the topic of Real Application Clusters (RAC)
implementation had never been fully explored. For the first time,
Murali Vallath dissects RAC mysteries in his book Oracle Real
Application Clusters to enlighten and educate readers on the
internals of RAC operations, cache fusion, fusion recovery
processes and the fast reconfiguration of RAC.
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.
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.
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.
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. |
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