Personalized Human Computer Interaction

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.

How do you design personalized user experiences that delight and provide value to the customers of an eCommerce site? Personalization does not guarantee high quality user experience: a personalized user experience has the best chance of success if it is developed using a set of best practices in HCI. In this book 35 experts from academia, industry and government focus on issues in the design of personalized web sites. The topics range from the design and evaluation of user interfaces and tools to information architecture and computer programming related to commercial web sites. The book covers four main areas: -Theoretical, Conceptual, and Architectural Frameworks of Personalization, -Research on the Design and Evaluation of Personalized User Experiences in Different Domains, -Approaches to personalization Through Recommender Systems, -Lessons Learned and Future Research Questions. This book will be a valuable tool in helping the reader to understand the range of factors to take into consideration in designing and building a personalized user experience. The authors of each of the chapters identify possibilities and alert the reader to issues that can be addressed in the beginning of a project by taking a 'big picture' view of designing personalized user interfaces. For anyone working or studying in the field of HCI, information architecture or eCommerce, this book will provide a solid foundation of knowledge and prepare for the challenges ahead.

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.

Personalization is ubiquitous from search engines to online-shopping websites helping us find content more efficiently and this book focuses on the key developments that are shaping our daily online experiences. With advances in the detection of end users’ emotions, personality, sentiment and social signals, researchers and practitioners now have the tools to build a new generation of personalized systems that will really understand the user’s state and deliver the right content. With leading experts from a vast array of domains from user modeling, mobile sensing and information retrieval to artificial intelligence, human-computer interaction (HCI) social computing and psychology, a broad spectrum of topics are covered. From discussing psychological theoretical models and exploring state-of-the-art methods for acquiring emotions and personality in an unobtrusive way, as well as describing how these concepts can be used to improve various aspects of the personalization process and chapters that discuss evaluation and privacy issues. Emotions and Personality in Personalized Systems will help aid researchers and practitioners develop and evaluate user-centric personalization systems that take into account the factors that have a tremendous impact on our decision-making – emotions and personality.

TV viewers today are exposed to overwhelming amounts of information, and challenged by the plethora of interactive functionality provided by current set-top boxes. To ensure broad adoption of this technology by consumers, future Digital Television will have to take usability issues thoroughly into account. In particular, serious attention must be paid to facilitate the selection of content on an individual basis, and to provide easy-to-use interfaces that satisfy viewers' interaction requirements. This volume collects selected research reports on the development of personalized services for Interactive TV. Drawing upon contributions from academia and industry in the US, Europe and Asia, this book represents a comprehensive picture of leading edge research in personalized television.

This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.