SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models

Simon Ott, Christian Meilicke, Matthias Samwald. SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models. In Danqi Chen, Jonathan Berant, Andrew McCallum, Sameer Singh 0001, editors, 3rd Conference on Automated Knowledge Base Construction, AKBC 2021, Virtual, October 4-8, 2021. 2021. [doi]

@inproceedings{OttMS21,
  title = {SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models},
  author = {Simon Ott and Christian Meilicke and Matthias Samwald},
  year = {2021},
  doi = {10.24432/C5MK57},
  url = {https://doi.org/10.24432/C5MK57},
  researchr = {https://researchr.org/publication/OttMS21},
  cites = {0},
  citedby = {0},
  booktitle = {3rd Conference on Automated Knowledge Base Construction, AKBC 2021, Virtual, October 4-8, 2021},
  editor = {Danqi Chen and Jonathan Berant and Andrew McCallum and Sameer Singh 0001},
}