Arts and Humanities Commons^™

Idiom Type Identification With Smoothed Lexical Features And A Maximum Margin Classifier, Giancarlo Salton, Robert J. Ross, John D. Kelleher

Conference papers

In our work we address limitations in the state-of-the-art in idiom type identification. We investigate different approaches for a lexical fixedness metric, a component of the state-of-the-art model. We also show that our Machine Learning based approach to the idiom type identification task achieves an F1-score of 0.85, an improvement of 11 points over the state-of-the-art.