  With the emergence of Smart TV and related interconnected devices, second
screen solutions have rapidly appeared to provide more content for end-users
and enrich their TV experience. Given the various data and sources involved -
videos, actors, social media and online databases- the aforementioned market
poses great challenges concerning user context management and sophisticated
recommendations that can be addressed to the end-users. This paper presents an
innovative Context Management model and a related first and second screen
recommendation service, based on a user-item graph analysis as well as
collaborative filtering techniques in the context of a Dynamic Social & Media
Content Syndication (SAM) platform. The model evaluation provided is based on
datasets collected online, presenting a comparative analysis concerning
efficiency and effectiveness of the current approach, and illustrating its
added value.
