… As the final step, we propose a novel Graph Transformer Network (GTN) architecture to …
two different users and recognizing a target user given their tweet sequence and social network …

… Graph Transformer Network (GTN) that learns to transform a heterogeneous input graph
into useful meta-path graphs for each task and learn node representation on the graphs in an …

… network user identification refers to finding users with the same identity in multiple social
networks… the node information and network structure information from the graph data form into …

… We propose a novel privacy-preserving graph transformer networks to achieve novel
performance with our privacy-preserving mechanisms. We apply our framework on the COCO …

… the graph connectivity inductive bias, and can perform poorly when the graph topology is …
We introduce a graph transformer with four new properties compared to the standard model. …

… the network structure information more comprehensively. Additionally, we propose to apply
the graph transformer network … Finally, we employ the graph convolutional network to classify …

… different sources to obtain user identity and private information. This technology can reveal
the … of graph neural networks, it is a current trend to extend neural networks to input a graph …

… For Bilibili, the user ID number is continuous, we apply the user ID to stitch the access address
and use this address to crawl the user profile, but there will be some links inaccessible, so …

… the performance of user recognition, this paper proposes HGT-PL, namely a Heterogeneous
Graph Transformer with … Then cluster methods are used to realize user recognition. Using …

… However, for extracting users’ preferences from the graph, it is a … detection using Graph
Transformer Network (GTN), which can learn efficient node representations while identifying …