In this paper we compare the effects of applying various state-of-the-art word representation strategies in the task of multi-word expression (MWE) identification. In particular, we analyze the strengths and weaknesses of the usage of 1-regularized sparse word embeddings for identifying MWEs. Our earlier study demonstrated the effectiveness of regularized word embeddings in other sequence labeling tasks, i.e. part-of-speech tagging and named entity recognition, but it has not yet been rigorously evaluated for the identification of MWEs yet.
REF in his own approach investigates the effect of 1 -regularized sparse word embeddings for identification of multi-word expressions.
ℓ1 Regularization of Word Embeddings for Multi-Word Expression Identification
Acta Cybern.
Acta Cybern.
Mathematics Computer Science