Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models. Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using semantic models as a basis for adaptive interactive systems. A variety of reasoning and machine learning techniques exist that can be employed to achieve adaptive system behavior. The advent and rapid growth of Linked Open Data as a large-scale collection of semantic data has also paved the way for a new breed of intelligent, knowledge-intensive applications. Semantic Models for Adaptive Interactive Systems includes ten complementary chapters written by experts from both industry and academia. Rounded off by a number of case studies in real world application domains, this book will serve as a valuable reference for researchers and practitioners exploring the use of semantic models within HCI.

This book gathers the latest experience of experts, research teams and leading organizations involved in computer-aided design of user interfaces of interactive applications. This area investigates how it is desirable and possible to support, to facilitate and to speed up the development life cycle of any interactive system. In particular, it stresses how the design activity could be better understood for different types of advanced interactive systems.

Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models. Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using semantic models as a basis for adaptive interactive systems. A variety of reasoning and machine learning techniques exist that can be employed to achieve adaptive system behavior. The advent and rapid growth of Linked Open Data as a large-scale collection of semantic data has also paved the way for a new breed of intelligent, knowledge-intensive applications. Semantic Models for Adaptive Interactive Systems includes ten complementary chapters written by experts from both industry and academia. Rounded off by a number of case studies in real world application domains, this book will serve as a valuable reference for researchers and practitioners exploring the use of semantic models within HCI.

This book gathers the latest experience of experts, research teams and leading organizations involved in computer-aided design of user interfaces of interactive applications. This area investigates how it is desirable and possible to support, to facilitate and to speed up the development life cycle of any interactive system: requirements engineering, early-stage design, detailed design, development, deployment, evaluation and maintenance. In particular, it stresses how the design activity could be better understood for different types of advanced interactive systems such as context-aware systems, multimodal applications, multi-platform systems, pervasive computing, ubiquitous computing and multi-device environments.