  To deal with irregular data structure, graph convolution neural networks have
been developed by a lot of data scientists. However, data scientists just have
concentrated primarily on developing deep neural network method for un-directed
graph. In this paper, we will present the novel neural network method for
directed hypergraph. In the other words, we will develop not only the novel
directed hypergraph neural network method but also the novel directed
hypergraph based semi-supervised learning method. These methods are employed to
solve the node classification task. The two datasets that are used in the
experiments are the cora and the citeseer datasets. Among the classic directed
graph based semi-supervised learning method, the novel directed hypergraph
based semi-supervised learning method, the novel directed hypergraph neural
network method that are utilized to solve this node classification task, we
recognize that the novel directed hypergraph neural network achieves the
highest accuracies.
