As the core layer of the Internet of Things (IoT), middleware bridges the gap between
applications and devices to resolve many common IoT issues and enhancing application …

Contextual Multi-Armed Bandit (CMAB) algorithms such as LinUCB (Linear Upper
Confidence Bound) or Contextual Thompson Sampling (CTS) base their resolution on the …

Collaborative and content-based recommender systems are widely employed in several
activity domains helping users in finding relevant products and services (ie, items). However …

Resumo A Internet das Coisas (IoT) é um conceito que conecta objetos inteligentes
equipados com sensores, redes e tecnologias de processamento que trabalham juntos para …

Contextual Multi-Armed Bandit (CMAB) algorithms suppose a linear dependency between
the expected reward of an action and its context. If given a complete and relevant context …

Passengers in public transport expect passenger information to be exact, timely and
appropriate to their situation. Therefore, future passenger information systems should adapt …

Any information used to characterize the situation of an entity: a person, a place, or an
object, can be considered as context. Indeed, context is crucial to avoid semantic ambiguity …

Resumen En esta Tesis Doctoral se presenta MAS-RECON, una plataforma genérica,
personalizable y extensible para la gestión del ciclo de ejecución de aplicaciones sensibles …

Les algorithmes de bandits-manchots pour les systèmes de recommandation sensibles au
contexte font aujourd'hui l'objet de nombreuses études. Afin de répondre aux enjeux de …

En raison du volume croissant de données disponibles, les systèmes de recommandation
sont de plus en plus utilisés et font l'objet de nombreuses recherches. Ils permettent de …