This book focuses on the importance of adaptation and personalization in today’s society and the upgraded role computational systems and the Internet play in our day-to-day activities. In this era of wireless communication, pervasive computing and the Internet of Things, it is becoming increasingly critical to ensure humans remain central in the developmental process of new technologies to guarantee their continued usefulness and a positive end-user experience. Organized into three clear parts - theory, principles and practice, a holistic approach to designing and developing adaptive interactive systems and services has been adopted. With an emphasis on distinct human factors, both basic and applied research topics are explored, extending from human-centred user models, driven by user’s individual differences in cognitive processing and emotions, to the creation of smart interfaces that can handle the ever increasing volume and complexity of information to the benefit of the end-user. Human-Centred Web Adaptation and Personalization – From Theory to Practice is meticulously crafted to serve researchers, practitioners, and students who wish to have an end-to-end understanding of how to convert pure research and scientific results into viable user interfaces, system components and applications. It will serve to bridge the knowledge gap that still remains by suggesting interaction design and implementation guidelines for areas like E-Commerce, E-Learning and Usable Security.

Personalized and adaptive systems employ user models to adapt content, services, interaction or navigation to individual users’ needs. User models can be inferred from implicitly observed information, such as the user’s interaction history or current location, or from explicitly entered information, such as user profile data or ratings. Applications of personalization include item recommendation, location-based services, learning assistance and the tailored selection of interaction modalities. With the transition from desktop computers to mobile devices and ubiquitous environments, the need for adapting to changing contexts is even more important. However, this also poses new challenges concerning privacy issues, user control, transparency, and explainability. In addition, user experience and other human factors are becoming increasingly important. This book describes foundations of user modeling, discusses user interaction as a basis for adaptivity, and showcases several personalization approaches in a variety of domains, including music recommendation, tourism, and accessible user interfaces.

Zusammenfassung: This book investigates the potential of combining the more quantitative - data-driven techniques with the more qualitative - theory-driven approaches towards the design of user-centred intelligent systems. It seeks to explore the potential of incorporating factors grounded in psychological theory into adaptive/intelligent routines, mechanisms, technologies and innovations. It highlights models, methods and tools that are emerging from their convergence along with challenges and lessons learned. Special emphasis is placed on promoting original insights and paradigms with respect to latest technologies, current research trends, and innovation directions, e.g., incorporating variables derived from psychological theory and individual differences in adaptive intelligent systems so as to increase explainability, fairness, and transparency, and decrease bias during interactions while the control remains with the user

When facilitating high-quality education, using digital technology to personalize students' learning is a focus in the development of instruction. There is a need to unify the multifaceted directions in personalized learning by presenting a coherent and organized vision in the design of personalized learning using digital technology. Digital Technologies and Instructional Design for Personalized Learning is a critical scholarly resource that highlights the theories, principles, and learning strategies in personalized learning with digital technology. Featuring coverage on a broad range of topics, such as collaborative learning, instructional design, and computer-supported collaborative learning, this book is geared towards educators, professionals, school administrators, academicians, researchers, and students seeking current research on the area of personalized learning with digital technology.

"This book identifies solutions and suggestions for the design and development of adaptive applications and systems that provides more usable and qualitative content and services adjusted to the needs and requirements of the various users"--Provided by publisher.

The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This third volume is dedicated to the interfaces of AI with various fields, with which strong links exist either at the methodological or at the applicative levels. The foreword of this volume reminds us that AI was born for a large part from cybernetics. Chapters are devoted to disciplines that are historically sisters of AI: natural language processing, pattern recognition and computer vision, and robotics. Also close and complementary to AI due to their direct links with information are databases, the semantic web, information retrieval and human-computer interaction. All these disciplines are privileged places for applications of AI methods. This is also the case for bioinformatics, biological modeling and computational neurosciences. The developments of AI have also led to a dialogue with theoretical computer science in particular regarding computability and complexity. Besides, AI research and findings have renewed philosophical and epistemological questions, while their cognitive validity raises questions to psychology. The volume also discusses some of the interactions between science and artistic creation in literature and in music. Lastly, an epilogue concludes the three volumes of this Guided Tour of AI Research by providing an overview of what has been achieved by AI, emphasizing AI as a science, and not just as an innovative technology, and trying to dispel some misunderstandings.