In this book, the authors first address the research issues by providing a motivating scenario, followed by the exploration of the principles and techniques of the challenging topics. Then they solve the raised research issues by developing a series of methodologies. More specifically, the authors study the query optimization and tackle the query performance prediction for knowledge retrieval. They also handle unstructured data processing, data clustering for knowledge extraction. To optimize the queries issued through interfaces against knowledge bases, the authors propose a cache-based optimization layer between consumers and the querying interface to facilitate the querying and solve the latency issue. The cache depends on a novel learning method that considers the querying patterns from individual's historical queries without having knowledge of the backing systems of the knowledge base. To predict the query performance for appropriate query scheduling, the authors examine the queries' structural and syntactical features and apply multiple widely adopted prediction models. Their feature modelling approach eschews the knowledge requirement on both the querying languages and system. To extract knowledge from unstructured Web sources, the authors examine two kinds of Web sources containing unstructured data: the source code from Web repositories and the posts in programming question-answering communities. They use natural language processing techniques to pre-process the source codes and obtain the natural language elements. Then they apply traditional knowledge extraction techniques to extract knowledge. For the data from programming question-answering communities, the authors make the attempt towards building programming knowledge base by starting with paraphrase identification problems and develop novel features to accurately identify duplicate posts. For domain specific knowledge extraction, the authors propose to use a clustering technique to separate knowledge into different groups. They focus on developing a new clustering algorithm that uses manifold constraints in the optimization task and achieves fast and accurate performance. For each model and approach presented in this dissertation, the authors have conducted extensive experiments to evaluate it using either public dataset or synthetic data they generated.

This book highlights practical quantum key distribution systems and research on the implementations of next-generation quantum communication, as well as photonic quantum device technologies. It discusses how the advances in quantum computing and quantum physics have allowed the building, launching and deploying of space exploration systems that are capable of more and more as they become smaller and lighter. It also presents theoretical and experimental research on the potential and limitations of secure communication and computation with quantum devices, and explores how security can be preserved in the presence of a quantum computer, and how to achieve long-distance quantum communication. The development of a real quantum computer is still in the early stages, but a number of research groups have investigated the theoretical possibilities of such computers.

ISGC 2009, The International Symposium on Grid Computing was held at Academia Sinica, Taipei, Taiwan in April 2009 bringing together prestigious scientists and engineers worldwide to exchange ideas, present challenges/solutions and introduce future development in the field of Grid Computing. Managed Grids and Cloud Systems in the Asia-Pacific Research Community presents the latest achievements in grid technology including Cloud Computing. This volume also covers international projects in Grid Operation, Grid Middleware, E-Science applications, technical developments in grid operations and management, Security and Networking, Digital Library and more. The resources used to support these advances, such as volunteer grids, production managed grids, and cloud systems are discussed in detail. This book is designed for a professional audience composed of grid users, developers and researchers working in the grid computing. Advanced-level students focusing on computer science and engineering will find this book valuable as a reference or secondary text book.

The issue of data quality is as old as data itself. Further, the proliferation of quite diverse (e.g. in terms of structure or media type) shared or public data on the Web has increased the risk of poor data quality and false data aggregation. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient IT tools and techniques related to record linkage, lineage and provenance, data uncertainty, and semantic integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.

Mobile communications and ubiquitous computing generate large volumes of data. Mining this data can produce useful knowledge, yet individual privacy is at risk. This book investigates the various scientific and technological issues of mobility data, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, and this book relates their findings in 13 chapters covering all related subjects.

Examples abound in database applications of well-formulated queries running slowly, even if all levels of the database are properly tuned. It is essential to address each level separately by focusing first on underlying principles and root causes, and only then proposing both theoretical and practical solutions. "Database Performance Tuning and Optimization" comprehensively addresses each level separately by focusing first on underlying principles and root causes, and then proposes both theoretical and practical solutions using Oracle 8i examples as the RDBMS. The book combines theory with practical tools (in the form of Oracle and UNIX shell scripts) to address the tuning and optimization issues of DBAs and developers, irrespective of whether they use Oracle. Topics and features: * An integrated approach to tuning by improving all three levels of a database (conceptual, internal, and external) for optimal performance * Balances theory with practice, developing underlying principles and then applying them to other RDBMSs, not just Oracle * Includes CD-ROM containing all scripts and methods utilized in the book * Coverage of data warehouses provides readers much needed principles and tools for tuning large reporting databases * Coverage of web-based databases * Appendix B shows how to create an instance and its associated database and all its objects * Provides useful exercises, references, and Oracle 8i and select 9i examples Based on nearly two decades of experience as an Oracle developer and DBA, the author delivers comprehensive coverage of the fundamental principles and methodologies of tuning and optimizing database performance. Database professionals and practitioners with some experience developing, implementing, and maintaining relational databases will find the work an essential resource. It is also suitable for professional short courses and self-study purposes.

New approaches are needed that could move us towards developing effective systems for problem solving and decision making, systems that can deal with complex and ill-structured situations, systems that can function in information rich environments, systems that can cope with imprecise information, systems that can rely on their knowledge and learn from experience - i.e. intelligent systems. One of the main efforts in intelligent systems development is focused on knowledge and information management which is regarded as the crucial issue in smart decision making support. The 13 Chapters of this book represent a sample of such effort. The overall aim of this book is to provide guidelines to develop tools for smart processing of knowledge and information. Still, the guide does not presume to give ultimate answers. Rather, it poses ideas and case studies to explore and the complexities and challenges of modern knowledge management issues. It also encourages its reader to become aware of the multifaceted interdisciplinary character of such issues. The premise of this book is that its reader will leave it with a heightened ability to think - in different ways - about developing, evaluating, and supporting intelligent knowledge and information management systems in real life based environment.

Brain Inspired Cognitive Systems - BICS 2010 aims to bring together leading scientists and engineers who use analytic and synthetic methods both to understand the astonishing processing properties of biological systems and specifically of the brain, and to exploit such knowledge to advance engineering methods to build artificial systems with higher levels of cognitive competence.

BICS is a meeting point of brain scientists and cognitive systems engineers where cross-domain ideas are fostered in the hope of getting emerging insights on the nature, operation and extractable capabilities of brains. This multiple approach is necessary because the progressively more accurate data about the brain is producing a growing need of a quantitative understanding and an associated capacity to manipulate this data and translate it into engineering applications rooted in sound theories.

BICS 2010 is intended for both researchers that aim to build brain inspired systems with higher cognitive competences, and for life scientists who use and develop mathematical and engineering approaches for a better understanding of complex biological systems like the brain.

Four major interlaced focal symposia are planned for this conference and these are organized into patterns that encourage cross-fertilization across the symposia topics. This emphasizes the role of BICS as a major meeting point for researchers and practitioners in the areas of biological and artificial cognitive systems. Debates across disciplines will enrich researchers with complementary perspectives from diverse scientific fields.

BICS 2010 will take place July 14-16, 2010, in Madrid, Spain.

Here is a thorough, not-overly-complex introduction to the three technical foundations for multimedia applications across the Internet: communications (principles, technologies and networking); compressive encoding of digital media; and Internet protocol and services. All the contributing systems elements are explained through descriptive text and numerous illustrative figures; the result is a book well-suited toward non-specialists, preferably with technical background, who need well-composed tutorial introductions to the three foundation areas. The text discusses the latest advances in digital audio and video encoding, optical and wireless communications technologies, high-speed access networks, and IP-based media streaming, all crucial enablers of the multimedia Internet.

Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues including Web crawling and indexing Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work painstaking, critical, and forward-looking readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort.
* A comprehensive, critical exploration of statistics-based attempts to make sense of Web Mining.
* Details the special challenges associated with analyzing unstructured and semi-structured data.
* Looks at how classical Information Retrieval techniques have been modified for use with Web data.
* Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning.
* Analyzes current applications for resource discovery and social network analysis.
* An excellent way to introduce students to especially vital applications of data mining and machine learning technology."

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites. This book covers a wide spectrum of techniques, model methodologies and theories on development and applications of GIS relative to the internet. It includes coverage of business process services, and integration of GIS into global enterprise information systems and service architectures. The world's experts in this emerging field present examples and case studies for location-based services, coastal restoration, urban planning, battlefield planning, rehearsal environmental analysis and assessment.

This book constitutes the refereed proceedings of the 36th IFIP TC 11 International Conference on Information Security and Privacy Protection, SEC 2021, held in Oslo, Norway, in June 2021.*The 28 full papers presented were carefully reviewed and selected from 112 submissions. The papers present novel research on theoretical and practical aspects of security and privacy protection in ICT systems. They are organized in topical sections on digital signatures; vulnerability management; covert channels and cryptography; application and system security; privacy; network security; machine learning for security; and security management. *The conference was held virtually.

This is the first book entirely devoted to providing a perspective on the state-of-the-art of cloud computing and energy services and the impact on designing sustainable systems. Cloud computing services provide an efficient approach for connecting infrastructures and can support sustainability in different ways. For example, the design of more efficient cloud services can contribute in reducing energy consumption and environmental impact. The chapters in this book address conceptual principles and illustrate the latest achievements and development updates concerning sustainable cloud and energy services. This book serves as a useful reference for advanced undergraduate students, graduate students and practitioners interested in the design, implementation and deployment of sustainable cloud based energy services. Professionals in the areas of power engineering, computer science, and environmental science and engineering will find value in the multidisciplinary approach to sustainable cloud and energy services presented in this book.

This book explores recent advances in the Internet of things (IoT) via advanced technologies and provides an overview of most aspects which are relevant for advance secure, distributed, decentralized blockchain technology in the Internet of things, their applications, and industry IoT. The book provides an in-depth analysis of the step-by-step evolution of IoT to create a change by enhancing the productivity of industries. It introduces how connected things, data, and their communication (data sharing) environment build a transparent, reliable, secure environment for people, processes, systems, and services with the help of blockchain technology.

The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and service-oriented computing in data-intensive applications. Techniques with respect to the support in the current cloud environments, major challenges, and future trends are covered in the last section of this book. A survey addressing the techniques and special requirements for building database services are provided in this book as well.

This edited book adopts a cognitive perspective to provide breadth and depth to state-of-the-art research related to understanding, analyzing, predicting and improving one of the most prominent and important classes of behavior of modern humans, information search. It is timely as the broader research area of cognitive computing and cognitive technology have recently attracted much attention, and there has been a surge in interest to develop systems and technology that are more compatible with human cognitive abilities. Divided into three interlocking sections, the first introduces the foundational concepts of information search from a cognitive computing perspective to highlight the research questions and approaches that are shared among the contributing authors. Relevant concepts from psychology, information and computing sciences are addressed. The second section discusses methods and tools that are used to understand and predict information search behavior and how the cognitive perspective can provide unique insights into the complexities of the behavior in various contexts. The final part highlights a number of areas of applications of which education and training, collaboration and conversational search interfaces are important ones. Understanding and Improving Information Search - A Cognitive Approach includes contributions from cognitive psychologists, information and computing scientists around the globe, including researchers from Europe (France, Netherlands, Germany), the US, and Asia (India, Japan), providing their unique but coherent perspectives to the core issues and questions most relevant to our current understanding of information search behavior and improving information search.

Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR systems.

This book gathers selected papers from the KES-IDT-2020 Conference, held as a Virtual Conference on June 17-19, 2020. The aim of the annual conference was to present and discuss the latest research results, and to generate new ideas in the field of intelligent decision-making. However, the range of topics discussed during the conference was definitely broader and covered methods in e.g. classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in such diverse areas as finance, cybersecurity, economics, health, management and transportation. The Problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as Intelligent Data Processing and its Applications High-Dimensional Data Analysis and its Applications Multi-Criteria Decision Analysis - Theory and Applications Large-Scale Systems for Intelligent Decision-Making and Knowledge Engineering Decision Technologies and Related Topics in Big Data Analysis of Social and Financial Issues Decision-Making Theory for Economics

This proceedings book presents selected papers from the 4th Conference on Signal and Information Processing, Networking and Computers (ICSINC) held in Qingdao, China on May 23-25, 2018. It focuses on the current research in a wide range of areas related to information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource anyone interested in this field.

These proceedings gather cutting-edge papers exploring the principles, techniques, and applications of Microservices in Big Data Analytics. The ICETCE-2019 is the latest installment in a successful series of annual conferences that began in 2011. Every year since, it has significantly contributed to the research community in the form of numerous high-quality research papers. This year, the conference's focus was on the highly relevant area of Microservices in Big Data Analytics.

Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others.
Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses.

Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting.

Fuzzy sets were first proposed by Lotfi Zadeh in his seminal paper [366] in 1965, and ever since have been a center of many discussions, fervently admired and condemned. Both proponents and opponents consider the argu ments pointless because none of them would step back from their territory. And stiH, discussions burst out from a single sparkle like a conference pa per or a message on some fuzzy-mail newsgroup. Here is an excerpt from an e-mail messagepostedin1993tofuzzy-mail@vexpert. dbai. twvien. ac. at. by somebody who signed "Dave". , . . . Why then the "logic" in "fuzzy logic"? I don't think anyone has successfully used fuzzy sets for logical inference, nor do I think anyone wiH. In my admittedly neophyte opinion, "fuzzy logic" is a misnomer, an oxymoron. (1 would be delighted to be proven wrong on that. ) . . . I carne to the fuzzy literature with an open mind (and open wal let), high hopes and keen interest. I am very much disiHusioned with "fuzzy" per se, but I did happen across some extremely interesting things along the way. " Dave, thanks for the nice quote! Enthusiastic on the surface, are not many of us suspicious deep down? In some books and journals the word fuzzy is religiously avoided: fuzzy set theory is viewed as a second-hand cheap trick whose aim is nothing else but to devalue good classical theories and open up the way to lazy ignorants and newcomers.

The book presents contributions on statistical models and methods applied, for both data science and SDGs, in one place. Measuring and controlling data of SDGs, data driven measurement of progress needs to be distributed to stakeholders. In this situation, the techniques used in data science, specially, in the big data analytics, play an important role rather than the traditional data gathering and manipulation techniques. This book fills this space through its twenty contributions. The contributions have been selected from those presented during the 7th International Conference on Data Science and Sustainable Development Goals organized by the Department of Statistics, University of Rajshahi, Bangladesh; and cover topics mainly on SDGs, bioinformatics, public health, medical informatics, environmental statistics, data science and machine learning. The contents of the volume would be useful to policymakers, researchers, government entities, civil society, and nonprofit organizations for monitoring and accelerating the progress of SDGs.

This book explores the nexus of Sustainability and Information Communication Technologies that are rapidly changing the way we live, learn, and do business. The monumental amount of energy required to power the Zeta byte of data traveling across the globe's billions of computers and mobile phones daily cannot be overstated. This ground-breaking reference examines the possibility that our evolving technologies may enable us to mitigate our global energy crisis, rather than adding to it. By connecting concepts and trends such as smart homes, big data, and the internet of things with their applications to sustainability, the authors suggest that emerging and ubiquitous technologies embedded in our daily lives may rightfully be considered as enabling solutions for our future sustainable development.

Physical processes, involving atomic phenomena, allow more and more precise time and frequency measurements. This progress is not possible without convenient processing of the respective raw data. This book describes the data processing at various levels: design of the time and frequency references, characterization of the time and frequency references, and applications involving precise time and/or frequency references.