Papers by Göran Kauermann

1 papers
Embedding Space Correlation as a Measure of Domain Similarity (2020.lrec-1)

Copied to clipboard

Challenge: Existing work on domain similarity using text-based features of corpus is limited by pre-trained word embeddings.
Approach: They propose a measure of domain similarity based on dimension-wise correlations between embedding spaces . they find a threshold at which the measure indicates that two corpora come from the same domain .
Outcome: The proposed measure can be used to determine which corpora are more similar to each other in a cross-domain sentiment detection task.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations