Attention Streams (AS) can be described as a semantic realtime attention tracker. Contrary to usual interest extraction approaches, AS analyses your interests as you navigate between pages. This process is totally transparent to the user since the tracking engine runs as a page background process. Attention Streams provides a simple application that uses these tags for querying different online services in realtime given your most important attentions streams. The application enables the user to discover new information based on its interests. Contrary to the existing recommendation services, AS can discovers content that fits the full user context based on his location and attention. AS does not rely on generic interests for finding recommendation but on the evolving interests of the user. As a consequence, AS is providing highly contextual and ambient recommendations that can be used for supporting the user activity. The passive recommendations minimize the explicit user interaction with the system thus avoiding the user distraction: the user can just check the system if he needs specific information since it is always updated with his current activity. Attention Streams were awarded the 3rd Prize in the AI Mashup Challenge at ESWC 2010

Seventh Framework Programme