86 research outputs found
Correlation-based Intrinsic Evaluation of Word Vector Representations
We introduce QVEC-CCA--an intrinsic evaluation metric for word vector
representations based on correlations of learned vectors with features
extracted from linguistic resources. We show that QVEC-CCA scores are an
effective proxy for a range of extrinsic semantic and syntactic tasks. We also
show that the proposed evaluation obtains higher and more consistent
correlations with downstream tasks, compared to existing approaches to
intrinsic evaluation of word vectors that are based on word similarity.Comment: RepEval 2016, 5 page
- …