Nature

Heterogeneous graph convolutional network for rumor detection with multi-level interactive fusion and graph reconstruction

With the rapid development of mobile Internet technology, online social networks are gradually integrated in people’s lives, entertainment and work. Rumor information appears accompanied by the ...
Nature

Information flow optimization for adaptive neighbor selection graph embedding

In the domain of heterogeneous graph representation learning, traditional methodologies often rely excessively on manually crafted meta-paths and neighbor aggregation mechanisms when faced with ...
EurekAlert!

D2-GCN: a graph convolutional network with dynamic disentanglement for node classification

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
EurekAlert!

Heterogeneous spatio-temporal graph contrastive learning for point-of-interest recommendation

As one of the most crucial topics in the recommendation system field, Point-of-Interest (POI) recommendation aims to recommending potential interesting POIs to users. Recently, graph neural networks ...
Design-Reuse

Placement of different type nodes in a Network-on-chip graph

Modern network-on-chip could include different types of nodes. Generally nodes that are of-chip external interconnections controllers – external nodes, are used in the system for I/O. Internal nodes ...