Since the information provided by the base predictors can be contradicting, we use ideas from ensemble learning (Dietterichl, 2002) to learn the most confident indicators and to exploit domain-dependent information revealed by document ratings.
instead of averaging base predictors, MEM integrates their features along with the available coarse-grained training data into a unified probabilistic model.