Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Abstract: Semi-supervised node classification with Graph Convolutional Network (GCN) is an attractive topic in social media analysis and applications. Recent studies show that GCN-based classification ...

The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them ...

Spectral algorithms are widely applied to data clustering problems, including finding communities or partitions in graphs and networks. We propose a way of encoding sparse data using a ...

In the study of the spectra of power-law graphs, there are basically two competing approaches. One is to prove analogues of Wigner's semicircle law, whereas the other predicts that the eigenvalues ...