LEADER 04099nam 22006015 450 001 9910855380903321 005 20251113181232.0 010 $a9783031551093 024 7 $a10.1007/978-3-031-55109-3 035 $a(CKB)31801781200041 035 $a(MiAaPQ)EBC31313109 035 $a(Au-PeEL)EBL31313109 035 $a(DE-He213)978-3-031-55109-3 035 $a(OCoLC)1433026883 035 $a(EXLCZ)9931801781200041 100 $a20240430d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA Human-Centered Perspective of Intelligent Personalized Environments and Systems /$fedited by Bruce Ferwerda, Mark Graus, Panagiotis Germanakos, Marko Tkal?i? 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (302 pages) 225 1 $aHuman?Computer Interaction Series,$x2524-4477 311 08$a9783031551086 320 $aIncludes bibliographical references. 327 $aPart I: Theory: Individual differences for intelligent personalized environments -- Human factors in user modeling for intelligent systems -- The role of human-centred ai in user modeling, adaptation, and personalization ? Models, frameworks, and paradigms -- Fairness and explainability for enabling trust in AI systems -- Part II: Method: User models driven from human factors, inferred from data -- Transparent music preference modeling and recommendation with a model of human memory theory -- Personalization and individual differences in business data analytics -- Inferring Eudaimonia and Hedonia from digital traces -- Computational methods to infer human factors for adaptation and personalization using eye tracking -- Part III: Practice: The human factors in the center of applications and domains -- Coarse-grained detection for personalized online learning interventions -- Psychologically-informed design of energy recommender systems: Are nudges still effective in tailored choice environments?- Personalized persuasive technologies in health and wellness: From theory to practice. 330 $aThis book investigates the potential of combining the more quantitative - data-driven techniques with the more qualitative - theory-driven approaches towards the design of user-centred intelligent systems. It seeks to explore the potential of incorporating factors grounded in psychological theory into adaptive/intelligent routines, mechanisms, technologies and innovations. It highlights models, methods and tools that are emerging from their convergence along with challenges and lessons learned. Special emphasis is placed on promoting original insights and paradigms with respect to latest technologies, current research trends, and innovation directions, e.g., incorporating variables derived from psychological theory and individual differences in adaptive intelligent systems so as to increase explainability, fairness, and transparency, and decrease bias during interactions while the control remains with the user. 410 0$aHuman?Computer Interaction Series,$x2524-4477 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aCognitive psychology 606 $aArtificial intelligence 606 $aUser Interfaces and Human Computer Interaction 606 $aCognitive Psychology 606 $aIntelligence Infrastructure 615 0$aUser interfaces (Computer systems) 615 0$aHuman-computer interaction. 615 0$aCognitive psychology. 615 0$aArtificial intelligence. 615 14$aUser Interfaces and Human Computer Interaction. 615 24$aCognitive Psychology. 615 24$aIntelligence Infrastructure. 676 $a004.019 702 $aFerwerda$b Bruce 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910855380903321 996 $aA Human-Centered Perspective of Intelligent Personalized Environments and Systems$94240854 997 $aUNINA