Most neural models directly learn compositions upon word embeddings, and are reported to be powerful enough to learn high-quality distributed representations without human intervention.
in sparse case, heuristic weighting techniques designed by humans are shown to be able to bring significant improvements over raw BOW representation (Wang and Manning, 2012;Martineau and Finin, 2009).