@inproceedings{c7e12f16a25f47519287641f6d2fd978,
title = "Idiom type identification with smoothed lexical features and a maximum margin classifier",
abstract = "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.",
keywords = "idiom type identification, lexical fixedness metric, Machine Learning, F1-score",
author = "Salton, {Giancarlo D.} and Ross, {Robert J.} and Kelleher, {John D.}",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics (ACL). All rights reserved.; 11th International Conference on Recent Advances in Natural Language Processing, RANLP 2017 ; Conference date: 02-09-2017 Through 08-09-2017",
year = "2017",
doi = "10.26615/978-954-452-049-6_083",
language = "English",
series = "International Conference Recent Advances in Natural Language Processing, RANLP",
publisher = "Incoma Ltd",
pages = "642--651",
editor = "Galia Angelova and Kalina Bontcheva and Ruslan Mitkov and Ivelina Nikolova and Irina Temnikova",
booktitle = "International Conference on Recent Advances in Natural Language Processing",
}