• FILTERING COMPONENT – This module exploits the user profile to suggest rel-
evant items by matching the profile representation against that of items to be
recommended. The result is a binary or continuous relevance judgment (com- puted using some similarity metrics [42]), the latter case resulting in a ranked list
of potentially interesting items. In the above mentioned example, the matching
is realized by computing the cosine similarity between the prototype vector and
the item vectors.