Tag: link prediction

A new hybrid architecture combining graph convolutions with a lite capsule network delivers an average 9.1 percent improvement in link ...

Researchers have developed MMA-HNS, a framework that keeps multimodal knowledge graph completion accurate even when the textual descriptions of entities ...

Researchers in Cyprus used classical machine learning and GraphSAGE-based graph representation learning to predict missing transmission links in COVID-19 infection ...

Researchers at Fuzhou University have developed RCGELM-AE, a graph embedding model that trains in closed form without gradient descent while ...

Spanish researchers have developed RRWK, a return random walk-based subgraph extraction method that preserves structural fidelity in dense graphs where ...

Researchers at China Jiliang University have combined fine-tuned large language models with graph attention networks to complete incomplete knowledge graphs ...

Researchers have developed DIRA, a model that combines dynamic entity embeddings with implicit relation-aware self-attention to significantly improve temporal knowledge ...

A new adversarial training method called MI-MKGC dynamically balances text, image, and structural information to predict missing facts in multimodal ...

Researchers have developed CurvBi, a framework that unites four-dimensional bicomplex algebra with Fisher-Rao-based Riemannian fusion to improve multimodal knowledge graph ...