zjunlp/OntoProtein

Rationale for choosing this loss function

jasperhyp opened this issue · 2 comments

Regarding your KE loss function, could you kindly provide some intuitions on why this specific loss function was chosen (given there are so many metric learning losses on KG)? A few relevant pieces of literature that you referenced would be appreciated.

Hi,

For the design of KE loss function, we refer to the loss function in the KEPLER [1] and TransE, and we think that TransE is an easy and effective KE method.

[1] KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation, 2021

Thank you! Very helpful.