While the "must-link" constraints described in the paper can be treated as features, due to their high precision, treating them as hard constraints (set ρ to a high value) is a safe and direct way to inject human knowledge into the learning model.
in the following, we briefly discuss how to solve the inference problem with these two types of constraints.