Efficient Context Management and Personalized User Recommendations in a Smart Social TV Environment

  • Fotis Aisopos
  • Angelos Valsamis
  • Alexandros Psychas
  • Andreas Menychtas
  • Theodora Varvarigou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10382)


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.


Smart TV recommendations Social media Second screen Context management Graph analysis 



This work has been supported by the SAM project and funded from the European Union’s 7th Framework Programme for research, technological development and demonstration under grant agreement no 611312.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fotis Aisopos
    • 1
  • Angelos Valsamis
    • 2
  • Alexandros Psychas
    • 1
  • Andreas Menychtas
    • 1
  • Theodora Varvarigou
    • 1
  1. 1.Distributed, Knowledge and Media Systems GroupNational Technical University of AthensAthensGreece
  2. 2.Department of Informatics and TelecommunicationsNational and Kapodistrian University of AthensAthensGreece

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