Aiming at the problem of sparse information distribution and lack of good correlation between data in the era of big data, this paper proposes a knowledge graph query and reasoning method based on ...

In recent years, with the public availability of AI tools, more people have become aware of how closely the inner workings of ...

Graph convolutional neural netwoks (GCNNs) have been emerged to handle graph-structured data in recent years. Most existing GCNNs are either spatial approaches working on neighborhood of each node, or ...