Although the methods proposed in the paper are demonstrated using syntactic trees, we note that similar approaches can be used to encode other types of tree structured information such as knowledge graphs and ontology relations.
instead of using a fixed embedding, we use Convolutional Neural Networks (CNN) to model character level embedding, which values can be changed during training (Kim, 2014).