While a naive approach would be to exploit the concept embeddings learned from the KB distributed representation <cite>[6,</cite> 18] as input of the deep neural network, we believe that a hybrid representation of the distributional semantic (namely, word embeddings) and the symbolic semantics (namely, concept embeddings taking into account the graph structure) would allow enhancing the document-query matching.