Corpus ID: 218487841

A Joint Framework for Inductive Representation Learning and Explainable Reasoning in Knowledge Graphs

@article{Bhowmik2020AJF,
  title={A Joint Framework for Inductive Representation Learning and Explainable Reasoning in Knowledge Graphs},
  author={Rajarshi Bhowmik and G. Melo},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.00637}
}
  • Rajarshi Bhowmik, G. Melo
  • Published 2020
  • Computer Science
  • ArXiv
  • Despite their large-scale coverage, existing cross-domain knowledge graphs invariably suffer from inherent incompleteness and sparsity, necessitating link prediction that requires inferring a target entity, given a source entity and a query relation. Recent approaches can broadly be classified into two categories: embedding-based approaches and path-based approaches. In contrast to embedding-based approaches, which operate in an uninterpretable latent semantic vector space of entities and… CONTINUE READING

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