Symbolic Graph Embedding Using Frequent Pattern Mining

@article{krlj2019SymbolicGE,
  title={Symbolic Graph Embedding Using Frequent Pattern Mining},
  author={Bla{\vz} {\vS}krlj and Nada Lavrac and Jan Kralj},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.13314}
}
Relational data mining is becoming ubiquitous in many fields of study. It offers insights into behaviour of complex, real-world systems which cannot be modeled directly using propositional learning. We propose Symbolic Graph Embedding (SGE), an algorithm aimed to learn symbolic node representations. Built on the ideas from the field of inductive logic programming, SGE first samples a given node’s neighborhood and interprets it as a transaction database, which is used for frequent pattern mining… 
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