Tenth International Workshop on Database and Expert Systems Applications


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Proceedings of the September 1999 workshop on defining requirements for future systems in the areas of database and artificial technologies. The 151 contributions discuss innovative applications and new architectures; mobility in databases and distributed systems; similarity search; web-based inform"




Very Large Data Bases


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Databases and Information Systems VII


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Conference held July 8-11, 2012, in Vilnius, Lithuania.




Very Large Data Bases


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Medical Image Databases


Book Description

Medical Image Databases covers the new technologies of biomedical imaging databases and their applications in clinical services, education, and research. Authors were selected because they are doing cutting-edge basic or technology work in relevant areas. This was done to infuse each chapter with ideas from people actively investigating and developing medical image databases rather than simply review the existing literature. The authors have analyzed the literature and have expanded on their own research. They have also addressed several common threads within their generic topics. These include system architecture, standards, information retrieval, data modeling, image visualizations, query languages, telematics, data mining, and decision supports. The new ideas and results reported in this volume suggest new and better ways to develop imaging databases and possibly lead us to the next information infrastructure in biomedicine. Medical Image Databases is suitable as a textbook for a graduate-level course on biomedical imaging or medical image databases, and as a reference for researchers and practitioners in industry.




Data Stream Management


Book Description

This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.




Broad Learning Through Fusions


Book Description

This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.




Multimedia Security


Book Description

Multimedia Security: Watermarking, Steganography, and Forensics outlines essential principles, technical information, and expert insights on multimedia security technology used to prove that content is authentic and has not been altered. Illustrating the need for improved content security as the Internet and digital multimedia applications rapidly evolve, this book presents a wealth of everyday protection application examples in fields including multimedia mining and classification, digital watermarking, steganography, and digital forensics. Giving readers an in-depth overview of different aspects of information security mechanisms and methods, this resource also serves as an instructional tool on how to use the fundamental theoretical framework required for the development of extensive advanced techniques. The presentation of several robust algorithms illustrates this framework, helping readers to quickly master and apply fundamental principles. Presented case studies cover: The execution (and feasibility) of techniques used to discover hidden knowledge by applying multimedia duplicate mining methods to large multimedia content Different types of image steganographic schemes based on vector quantization Techniques used to detect changes in human motion behavior and to classify different types of small-group motion behavior Useful for students, researchers, and professionals, this book consists of a variety of technical tutorials that offer an abundance of graphs and examples to powerfully convey the principles of multimedia security and steganography. Imparting the extensive experience of the contributors, this approach simplifies problems, helping readers more easily understand even the most complicated theories. It also enables them to uncover novel concepts involved in the implementation of algorithms, which can lead to the discovery of new problems and new means of solving them.




Proceedings of the 7th International Conference on Emerging Databases


Book Description

This proceedings volume presents selected papers from the 7th International Conference on Emerging Databases: Technologies, Applications, and Theory (EDB 2017), which was held in Busan, Korea from 7 to 9 August, 2017. This conference series was launched by the Korean Institute of Information Scientists and Engineers (KIISE) Database Society of Korea as an annual forum for exploring novel technologies, applications, and research advances in the field of emerging databases. This forum has evolved into the premier international venue for researchers and practitioners to discuss current research issues, challenges, new technologies, and solutions.