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| Author | : Elisabeth Lex |
| Publisher | : |
| Total Pages | : 122 |
| Release | : 2021-07-15 |
| Genre | : |
| ISBN | : 9781680838442 |
This survey presents a thorough review of the state of the art of recommender systems that leverage psychological constructs and theories to model and predict user behavior and improve the recommendation process - so-called psychology-informed recommender systems.
| Author | : Francesco Ricci |
| Publisher | : Springer Nature |
| Total Pages | : 1053 |
| Release | : 2022-04-21 |
| Genre | : Computers |
| ISBN | : 1071621971 |
This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool.
| Author | : Bruce Ferwerda |
| Publisher | : Springer Nature |
| Total Pages | : 304 |
| Release | : |
| Genre | : Human-computer interaction |
| ISBN | : 3031551095 |
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
| Author | : Maria Augusta Silveira Netto Nunes |
| Publisher | : |
| Total Pages | : 148 |
| Release | : 2009-06-01 |
| Genre | : Computers |
| ISBN | : 9783639169768 |
The World Wide Web is a great source of products and services available to people. Scientists have made a huge effort to create effective strategies to personalize those products/services for anyone willing to use them. The personalization may be provided by Recommender Systems which are able to match people's preferences to specific products or services. Scientists from different research areas such as Psychology, Neurology and Affective Computing agree that human reasoning and decision-making are hardly ever affected by psychological aspects. Thus, to maintain the same level of personalized service provided by humans, computers should also ``reason", taking into account users' psychological aspects. Nevertheless, the psychological aspects have, unfortunately, not been highly applied in most models of User Profiles used in Recommender Systems. As a result, the existing Recommender Systems do not actually use psychological aspects such as Personality Traits during their decision-making process in order to generate their recommendations. In this thesis we propose the implementation of the Personality Traits in User Profiles so it is possible to obtain evidence that the use of Personality Traits in Recommender Systems might be coherent and effective for the improvement of the recommendations for users and, therefore, act proactively towards users' needs, offering more adaptable products and services according to their future needs
| Author | : Alexander Felfernig |
| Publisher | : Springer Nature |
| Total Pages | : 180 |
| Release | : 2023-11-27 |
| Genre | : Technology & Engineering |
| ISBN | : 3031449436 |
This book discusses different aspects of group recommender systems, which are systems that help to identify recommendations for groups instead of single users. In this context, the authors present different related techniques and applications. The book includes in-depth summaries of group recommendation algorithms, related industrial applications, different aspects of preference construction and explanations, user interface aspects of group recommender systems, and related psychological aspects that play a crucial role in group decision scenarios.
| Author | : Kyung-Hyan Yoo |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 62 |
| Release | : 2012-08-17 |
| Genre | : Computers |
| ISBN | : 146144702X |
Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding influential factors in advice seeking relationships, which is abundant in the context of human-human relationships, can provide an important framework for identifying potential influence factors in recommender system context. This book reviews the existing literature on the factors in advice seeking relationships in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.
| Author | : Francesco Ricci |
| Publisher | : Springer |
| Total Pages | : 1008 |
| Release | : 2015-11-17 |
| Genre | : Computers |
| ISBN | : 148997637X |
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.
| Author | : Hannes Werthner |
| Publisher | : Springer Nature |
| Total Pages | : 631 |
| Release | : 2024-01-21 |
| Genre | : Computers |
| ISBN | : 3031453042 |
This open access textbook introduces and defines digital humanism from a diverse range of disciplines. Following the 2019 Vienna Manifesto, the book calls for a digital humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights. The book is organized in three parts: Part I “Background” provides the multidisciplinary background needed to understand digital humanism in its philosophical, cultural, technological, historical, social, and economic dimensions. The goal is to present the necessary knowledge upon which an effective interdisciplinary discourse on digital humanism can be founded. Part II “Digital Humanism – a System’s View” focuses on an in-depth presentation and discussion of the main digital humanism concerns arising in current digital systems. The goal of this part is to make readers aware and sensitive to these issues, including e.g. the control and autonomy of AI systems, privacy and security, and the role of governance. Part III “Critical and Societal Issues of Digital Systems” delves into critical societal issues raised by advances of digital technologies. While the public debate in the past has often focused on them separately, especially when they became visible through sensational events the aim here is to shed light on the entire landscape and show their interconnected relationships. This includes issues such as AI and ethics, fairness and bias, privacy and surveillance, platform power and democracy. This textbook is intended for students, teachers, and policy makers interested in digital humanism. It is designed for stand-alone and for complementary courses in computer science, or curricula in science, engineering, humanities and social sciences. Each chapter includes questions for students and an annotated reading list to dive deeper into the associated chapter material. The book aims to provide readers with as wide an exposure as possible to digital advances and their consequences for humanity. It includes constructive ideas and approaches that seek to ensure that our collective digital future is determined through human agency.
| Author | : Charu C. Aggarwal |
| Publisher | : Springer |
| Total Pages | : 518 |
| Release | : 2016-03-28 |
| Genre | : Computers |
| ISBN | : 3319296590 |
This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.
| Author | : Mirjam Augstein |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 442 |
| Release | : 2023-08-07 |
| Genre | : Computers |
| ISBN | : 3110988771 |
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.
