Efficient Context Management and Personalized User Recommendations in a Smart Social TV environment
arXiv:1707.02546 · doi:10.1007/978-3-319-61920-0_8
Abstract
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.
In GECON2016, 13th International Conference on Economics of Grids, Clouds, Systems, and Services, September 20-22, 2016, Harokopio University, Athens, Greece