Bøger i Advanced Information and Knowledge Processing serien

The need for this resolution of knowledge inconsistency arises in many practical applications of computer systems. This kind of inconsistency results from the use of various resources of knowledge in realizing practical tasks. These resources are often autonomous and use different mechanisms for processing knowledge about the same real world.

Mathematical Linguistics introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing. The book presents linguistics as a cumulative body of knowledge from the ground up: no prior knowledge of linguistics is assumed.

For - ample, since the 1940s, there have appeared systems theory, information theory, fuzzy mathematics, cybernetics, dissipative structures, synergetics, catastrophe theory, chaos theory, bifurcations, ultra circulations, dynamics, and many other systems theories.

Multi-database mining has been recognized as a strategically essential area of research in data mining. This book discusses various issues regarding the systematic and efficient development of multi-database mining applications.

This monograph focuses on exploring game theoretic modeling and mechanism design for problem solving in Internet and network economics. For the first time, the main theoretical issues and applications of mechanism design are bound together in a single text.

Space support in databases poses new challenges in every part of a database management system & the capability of spatial support in the physical layer is considered very important.

Enhances the use of enterprise models as an effective communication medium between business and technical personnel. Details the blue-print of the to-be developed business system.

This book provides a comprehensive analysis of meta-programming, focusing on insights of meta-programming techniques, heterogeneous meta-program development processes in the context of model-driven, feature-based and transformative approaches.

Details research in areas such as ontology design for information integration, metadata generation and management, and representation and management of distributed ontologies. This title provides decision support on the use of novel technologies, information about potential problems, and guidelines for the application of existing technologies.

Covers the transmission of real-time video and audio for internet experimentation. Provides detailed descriptions of how the various hardware and software systems can be seamlessly integrated for a complete internet remote experimentation system. Contains examples of real working experiments that are currently running.

The European Commission facilitates and supports applied research in knowledge management through its Information Society Technologies (1ST) programme, a major theme of research and technological development within the European Union's Research and Technology Development Framework Programme.

Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them.

This book illustrates how to deal with complex media and convert raw data into useful information. Students and researchers needing a solid foundation or reference, and practitioners interested in discovering more about the state-of-the-art will find this book invaluable.

Data science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety of disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, business, and the humanities.

The motivation of this edited book is to generate an understanding about information, related concepts and the roles they play in the modern, technology permeated world. In order to achieve our goal, we observe how information is understood in domains, such as cosmology, physics, biology, neuroscience, computer science, artificial intelligence, the Internet, big data, information society, or philosophy. Together, these observations form an integrated view so that readers can better understand this exciting building-block of modern-day society.On the surface, information is a relatively straightforward and intuitive concept. Underneath, however, information is a relatively versatile and mysterious entity. For instance, the way a physicist looks at information is not necessarily the same way as that of a biologist, a neuroscientist, a computer scientist, or a philosopher. Actually, when it comes to information, it is common that each field has its domain specific views, motivations, interpretations, definitions, methods, technologies, and challenges.With contributions by authors from a wide range of backgrounds, Understanding Information: From the Big Bang to Big Data will appeal to readers interested in the impact of 'information' on modern-day life from a variety of perspectives.

The purpose of this book is to review the recent advances in E-health technologies and applications.

Social media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big data:Basic knowledge (data & challenges) on social media analyticsClustering as a fundamental technique for unsupervised knowledge discovery and data miningA class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges in big social media data clustering Step-by-step practices of developing unsupervised machine learning algorithms for real-world applications in social media domainAdaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction.It presents initiatives on the mathematical demonstration of ART's learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks.Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for you:How to process big streams of multimedia data?How to analyze social networks with heterogeneous data?How to understand a user's interests by learning from online posts and behaviors?How to create a personalized search engine by automatically indexing and searching multimodal information resources? .

This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms.

This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers' understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

In many recent application situations, however, the size of the input data is too large to fit within memory.Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications.

Introduced in the early 1980s, Rough Set Theory has become an important part of soft computing in the last 25 years. This book provides a practical, context-based analysis of rough set theory, with each chapter exploring a real-world application of Rough Sets.

A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the world's leading groups in the area of Bayesian identification, control, and decision making.

Section 2 explores other research and development projects that attempt to exploit the power of contemporary ICT systems to support Law Enforcement Agencies in many aspects of their work including investigations, data analysis and presentation, identification, training and crime prevention.

II Challenges in Data Mapping Part II deals with one of the most challenging tasks in Interactive Visualization, mapping and teasing out information from large complex datasets and generating visual representations.

Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.

This volume demonstrates the practical relevance and applicability of self-organization. It includes case studies that examine applications of self-organization, identify causes for their successes, and propose guiding principles for future developments.

Knowledge Cartography

The motivation of this edited book is to generate an understanding about information, related concepts and the roles they play in the modern, technology permeated world. In order to achieve our goal, we observe how information is understood in domains, such as cosmology, physics, biology, neuroscience, computer science, artificial intelligence, the Internet, big data, information society, or philosophy. Together, these observations form an integrated view so that readers can better understand this exciting building-block of modern-day society.On the surface, information is a relatively straightforward and intuitive concept. Underneath, however, information is a relatively versatile and mysterious entity. For instance, the way a physicist looks at information is not necessarily the same way as that of a biologist, a neuroscientist, a computer scientist, or a philosopher. Actually, when it comes to information, it is common that each field has its domain specific views, motivations, interpretations, definitions, methods, technologies, and challenges.With contributions by authors from a wide range of backgrounds, Understanding Information: From the Big Bang to Big Data will appeal to readers interested in the impact of ¿information¿ on modern-day life from a variety of perspectives.

Relatively new research ?elds such as ambient intelligence, intelligent envir- ments, ubiquitous computing, and wearable devices have emerged in recent years.