Tag: Graph Neural Networks

A new graph-based framework groups similar learners and augments sparse data to improve cognitive diagnosis predictions across three public datasets.

Researchers have built a Spark GraphFrames framework that enumerates millions of transaction cycles and filters them with timestamp and amount ...

A new contrastive learning framework called VMCL improves knowledge graph embedding for unseen entities and shows smooth, predictable gains as ...

A controlled comparison of ten graph neural network architectures finds that PNA, GAT, GCN, and EvolveGCN produce embedding spaces associated ...

A new recommender framework replaces single user and item embeddings with shared multi-aspect pools, improving accuracy across six datasets.

A new open-access study in Discover Computing presents CMCBI, a recommendation framework that aligns corporate financial signals with consumer behavior ...

A new study reports that a transparent, feature-based framework can detect rumors on social media with accuracy close to that ...

Researchers have introduced HOFA, a contrastive learning framework that mines triangular motifs in social networks and aligns embedding features to ...

A dynamic graph attention model published in Financial Innovation predicts how financial risk spreads through supply chain networks, outperforming static ...

Researchers have introduced cMSEDN, a deterministic method that turns multiscale EDN sequence representations into sequence-specific node embeddings for De Bruijn ...