Improve content recommendation

Develop new content recommendation tools.

Improve the user experience

Enhance the user experience based on their profile and environment.

Expected results

The PICAE project aims to make a qualitative leap in state-of-the-art TV and editorial content recommendation based on the following lines of research:

  • Development of models and analytical tools to facilitate the construction of user-profiles adapted to the field of audiovisual consumption (particularly TV) and editorial content.
  • Development of next-generation tools for indexing audio, images and text-based information to provide useful data for content recommendation.
  • Enhanced recommendation systems to embrace the broad range of parameters to be introduced through the generation of hybrid recommendation engines (collaborative and content-based).
  • Development, with diverse expert actors from the media field, of a technical recommendation platform capable of integrating indexing and user profiling.
  • Modelling of the impact on consumers/users and on business models using engagement generation and advertising to make a qualitative leap appropriate to the new consumption patterns in today’s society.

Participating companies and entities:

Lead company/entity:



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