Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings. (arXiv:2201.05575v1 [cs.CL])

Previous knowledge graph embedding approaches usually map entities to
representations and utilize score functions to predict the target entities, yet
they struggle to reason rare or emerging unseen entities. In this paper, we
propose kNN-KGE, a new knowledge graph embedding approach, by linearly
interpolating its entity distribution with k-nearest neighbors. We compute the
nearest neighbors based on the distance in the entity embedding space from the
knowledge store. Our approach can allow rare or emerging entities to be
memorized explicitly …

arxiv graph knowledge graph reasoning