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 . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.