  Weighted graphs obtained from co-occurrence in user-item relations lead to
non-metric topologies. We use this semi-metric behavior to issue
recommendations, and discuss its relationship to transitive closure on fuzzy
graphs. Finally, we test the performance of this method against other item- and
user-based recommender systems on the Movielens benchmark. We show that
including highly semi-metric edges in our recommendation algorithms leads to
better recommendations.
