Recursive Neural Networks for Processing Graphs with Labelled Edges

In this paper, we propose a new recursive neural network model, able to process directed acyclic graphs with labelled edges. The model is based on a different definition of the state transition function, which is independent both from the number and the order of the children of each node. In fact, the particular contribution of each child is encoded in the label attached to the corresponding edge. The computational capabilities of the new recursive architecture are also assessed.