Global information retrieval and anywhere, anytime information access has stimulated a need to design and model the personalized information search in a flexible and agile way that can use the specific personalization techniques, algorithms, and available technology infrastructure to satisfy high-level functional requirements for personalization. Personalized Information Retrieval and Access: Concepts, Methods and Practices surveys the main concepts, methods, and practices of personalized information retrieval and access in today's data intensive, dynamic, and distributed environment, and provides students, researchers, and practitioners with authoritative coverage of recent technological advances that are shaping the future of globally distributed information retrieval and anywhere, anytime information access.

Semantics in Adaptive and Personalised Services, initially strikes one as a specific and perhaps narrow domain. Yet, a closer examination of the term reveals much more. On one hand there is the issue of semantics. Nowadays, this most often refers to the use of OWL, RDF or some other XML based ontology description language in order to represent the entities of problem. Still, semantics may also very well refer to the consideration of the meanings and concepts, rather than arithmetic measures, regardless of the representation used. On the other hand, there is the issue of adaptation, i.e. automated re-configuration based on some context. This could be the network and device context, the application context or the user context; we refer to the latter case as personalization. From a different perspective, there is the issue of the point of view from which to examine the topic. There is the point of view of tools, referring to the algorithms and software tools one can use, the point of view of the methods, referring to the abstract methodologies and best practices one can follow, as well as the point of view of applications, referring to successful and pioneering case studies that lead the way in research and innovation. Or at least so we thought. Based on the above reasoning, the editors identified key researchers and practitioners in each of the aforementioned categories and invited them to contribute a corresponding work to this book. However, as the authors’ contributions started to arrive, the editors also started to realize that although these categories participate in each chapter to different degrees, none of them can ever be totally obsolete from them. Moreover, it seems that theory and methods are inherent in the development of tools and applications and inversely the application is also inherent in the motivation and presentation of tools and methods.

Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field.

"This publication covers the latest innovative research findings involved with the incorporation of technologies into everyday aspects of life"--Provided by publisher.

Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: • Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. • Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy through metasynthetic engineering. • Explains the concept and methodology of human-centred, human-machine-cooperated qualitative-to-quantitative metasynthesis for understanding and managing open complex giant systems, and its computing approach: metasynthetic computing. • Introduces techniques and tools for analysing and designing problem-solving systems for open complex problems and systems. Metasynthetic Computing and Engineering uses the systematology methodology in addressing system complexities in open complex giant systems, for which it may not only be effective to apply reductionism or holism. The book aims to encourage and inspire discussions, design, implementation and reflection of effective methodologies and tools for computing and engineering open complex systems and problems. Researchers, research students and practitioners in complex systems, artificial intelligence, data science, computer science, and even system science, cognitive science, behaviour science, and social science, will find this book invaluable.

Provides research developments on mobile technologies and services. Explains how users of such applications access intelligent and adaptable information services, maximizing convenience and minimizing intrusion.

The development of nature-inspired computational techniques has enhanced problem solving in dynamic and uncertain environments. By implementing effective computing strategies, this ensures adaptable, self-organizing, and decentralized behavioral techniques. Recent Developments in Intelligent Nature-Inspired Computing is an authoritative reference source for the latest scholarly material on natural computation methods and applications in diverse fields. Highlighting multidisciplinary studies on swarm intelligence, global optimization, and group technology, this publication is an ideal reference source for professionals, researchers, scholars, and engineers interested in the latest developments in computer science methodologies.

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments. Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included. Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.

"This book explores the latest empirical research and best real-world practices for preventing, weathering, and recovering from disasters such as earthquakes or tsunamis to nuclear disasters and cyber terrorism"--Provided by publisher.