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EU Project - Revelance and cognition for self-awareness in a content-centric Internet (RECOGNITION)

Contraente: Comunità Europea

Tipo: Progetto internazionale

Ubiquitous Internet

RECOGNITION will develop a radically new approach for embedding self-awareness in ICT systems. The innovative approach of the project is two-fold. Firstly we develop the concept of cognitive self-awareness at the device, at the artefact and at the system level, as a fundamental property of future ICT systems. This will be based on the cognitive processes that the human species exhibits for self-awareness, seeking to exploit the fact that humans are ultimately the fundamental basis for high performance autonomic processes. This is due to the cognitive ability of the brain to efficiently assert relevance (or irrelevance), extract knowledge and take appropriate decisions, when faced with partial information and disparate stimuli. Using the psychological and cognitive sciences as concrete inspiration, our approach is to develop functional models of the core cognitive processes that allow humans to assert relevance and achieve knowledge from information through mechanisms such as inference, belief, similarity and trust. This will be translated to the ICT domain by development of flexible RECOGNITION algorithms for self-aware autonomic nodes.
Secondly we will engage and demonstrate this cognitive self-awareness paradigm for new content-centric functionality. The future Internet will see ever-increasing amounts of content that needs to be effectively managed and acquired. Due to the long tail of user interests and widespread environmental data, the massive scale of content will swamp the user with information, impeding effective management and acquisition. By exploiting the self-awareness capability of our proposed novel content management solutions we will enable the users, content and network to cope effectively in a scalable manner, thus making unprecedented amounts of relevant content available and unleashing new classes of applications that extract maximum utility from content.


Dal 01/10/2010 al 30/09/2013