Knowledge Graph Embeddings
71 papers with code • 0 benchmarks • 2 datasets
These leaderboards are used to track progress in Knowledge Graph Embeddings
LibrariesUse these libraries to find Knowledge Graph Embeddings models and implementations
HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy.
This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks.
Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph as an independent graph language and propose an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.
Furthermore, we have implemented a fine-tuning architecture that adapts the knowledge graph embeddings to the effect prediction task and leads to better performance.
Many recent works have demonstrated the benefits of knowledge graph embeddings in completing monolingual knowledge graphs.
To model both structured knowledge and unstructured language, we propose a neural model with dynamic knowledge graph embeddings that evolve as the dialogue progresses.