C-norm: a neural approach to few-shot entity normalization

HIGHLIGHTS

  • who: Arnaud Ferré from the Université ParisSaclay, INRAE, MaIAGE, Jouy‑en‑Josas, France have published the research: C-Norm: a neural approach to few-shot entity normalization, in the Journal: (JOURNAL)
  • what: The authors propose C-Norm a new neural approach which synergistically combines standard and weak supervision ontological knowledge integration and distributional semantics. The authors propose C-Norm ("Concept-NORMalization"), a new shallow neural method to address the few-shot learning normalization problem. The authors design a new method that integrates the two approaches in an ensemble averaging way and compare its performance to . . .

     

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