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Apologies if you received multiple cross-postings of this CFP. ****************************************************************************************************** Call for Papers Special Issue "Recommender Systems and Technologies in Artificial Intelligence" Website: https://www.mdpi.com/journal/electronics/special_issues/RST Deadline for manuscript submissions: 15 December 2021 ****************************************************************************************************** Dear Colleagues, Today, thanks to an increasingly wider range of context-aware sensing opportunities, the user can be provided with modulated sensorial support in their performance. This increases the scope of building recommender systems aimed at providing emotion-aware recommendations within different ambient intelligence frameworks. In particular, there is strong evidence from previous research that emotions have an important effect on a user's performance in different tasks and contexts, where their mental state and subsequent behaviour present challenges for the successful deployment of automated or semi-automated systems. This covers a wide range of development areas, from self-driving cars to recommender systems in education and to intelligence guidance and coaching health professionals. This special Issue addresses the problem of detecting, modelling and reacting to those mental states of each user, which affect their readiness and disposition to cooperate with the system in achieving higher success and performance rates. It is particularly interested in papers that either provide evidence that detecting each user's emotions, behaviour, context and reactions makes a difference or show progress in building accurate, user-centred recommender systems that take advantage of an increasing number of data for each user in different scenarios and tasks, bearing in mind that the real problem is to model the user within them. Topics of interest include but are not limited to: * Wearable-based affect-recognition systems; * Affect-recognition systems from low-cost, off-the-shelf devices; * Sensor data quality assessment and management; * Multimodal affect-recognition systems; * Unobtrusive affect-recognition systems; * Machine-learning/artificial-intelligence approaches to obtaining personalized models for affect recognition; * Intelligent recommender systems in user-centred scenarios (e.g., medicine, education, transportation..); * Context-aware recommendation systems; * Methods and tools for affect-aware intelligent tutoring systems; * Behavioural interventions; * Adaptive systems that improve the performance of the user; * Affect-aware user models in semi-automated systems; * Experimental datasets; * Regulations and standards; * Privacy and ethics regarding user-centred recommender systems. In case you need any further information, please never hesitate to contact us or the Editorial Office: informat...@mdpi.com<mailto:informat...@mdpi.com>. Thank you very much in advance for your kind support and cooperation. We look forward to collaborating with you and to hearing back from you soon. Best Regards, Editors: Prof. Dr. Jesús G. Boticario, Prof. Dr. David Martín Gómez, Dr. Ana Serrano Mamolar AVISO LEGAL. Este mensaje puede contener información reservada y confidencial. Si usted no es el destinatario no está autorizado a copiar, reproducir o distribuir este mensaje ni su contenido. Si ha recibido este mensaje por error, le rogamos que lo notifique al remitente. Le informamos de que sus datos personales, que puedan constar en este mensaje, serán tratados en calidad de responsable de tratamiento por la UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA (UNED) c/ Bravo Murillo, 38, 28015-MADRID-, con la finalidad de mantener el contacto con usted. La base jurídica que legitima este tratamiento, será su consentimiento, el interés legítimo o la necesidad para gestionar una relación contractual o similar. En cualquier momento podrá ejercer sus derechos de acceso, rectificación, supresión, oposición, limitación al tratamiento o portabilidad de los datos, ante la UNED, Departamento de Política Jurídica de Seguridad de la Información<https://www.uned.es/dpj>, o a través de la Sede electrónica<https://sede.uned.es/> de la Universidad. Para más información visite nuestra Política de Privacidad<https://descargas.uned.es/publico/pdf/Politica_privacidad_UNED.pdf>.
