EEXCESS Recommender

The overall approach of the EEXCESS project is to ‘inject’ digital content (both metadata and object files) into users' daily environments like browsers, authoring environments like content management systems or Google Docs, or e-learning environments. Content is not just provided, but recommended by means of an organizational and technical framework of distributed partner recommenders and user profiles.

Project Details
Name:  EEXCESS Recommender  
Short Description:  A technical framework for recommending and accessing libraries' content  
Project Lead:  Timo Borst  
Categories:  Recommender system   Plug-in (computing)  
Created:  2016-06  
Project Status:  Production