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

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

16 September 2021
Simon Ott
Christian Meilicke
Matthias Samwald
    AI4CE
ArXivPDFHTML

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

3 / 3 papers shown
Title
PathE: Leveraging Entity-Agnostic Paths for Parameter-Efficient Knowledge Graph Embeddings
PathE: Leveraging Entity-Agnostic Paths for Parameter-Efficient Knowledge Graph Embeddings
Ioannis Reklos
Jacopo de Berardinis
Elena Simperl
Albert Meroño-Peñuela
236
0
0
31 Jan 2025
Emulating the Human Mind: A Neural-symbolic Link Prediction Model with
  Fast and Slow Reasoning and Filtered Rules
Emulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules
Mohammad Hossein Khojasteh
Najmeh Torabian
Ali Farjami
Saeid Hosseini
B. Minaei-Bidgoli
LRM
30
0
0
21 Oct 2023
Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey
Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey
L. Delong
Ramon Fernández Mir
Jacques D. Fleuriot
NAI
37
12
0
14 Feb 2023
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