@inproceedings{b0441716529f4fe4911b636e7298dd00,
title = "A simple word embedding model for lexical substitution",
abstract = "The lexical substitution task requires identifying meaning-preserving substitutes for a target word instance in a given sentential context. Since its introduction in SemEval-2007, various models addressed this challenge, mostly in an unsupervised setting. In this work we propose a simple model for lexical substitution, which is based on the popular skip-gram word embedding model. The novelty of our approach is in leveraging explicitly the context embeddings generated within the skip-gram model, which were so far considered only as an internal component of the learning process. Our model is efficient, very simple to implement, and at the same time achieves state-of-the-art results on lexical substitution tasks in an unsupervised setting.",
author = "Oren Melamud and Omer Levy and Ido Dagan",
note = "Publisher Copyright: {\textcopyright} 2015 The North American Chapter of the Association for Computational Linguistics.; 1st Workshop on Vector Space Modeling for Natural Language Processing, VS 2015 at the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 ; Conference date: 05-06-2015",
year = "2015",
doi = "https://doi.org/10.3115/v1/W15-1501",
language = "الإنجليزيّة",
series = "1st Workshop on Vector Space Modeling for Natural Language Processing, VS 2015 at the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015",
publisher = "Association for Computational Linguistics (ACL)",
pages = "1--7",
editor = "Phil Blunsom and Shay Cohen and Paramveer Dhillon and Percy Liang",
booktitle = "Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, VS 2015 at the Conference of the North American Chapter of the Association for Computational Linguistics",
address = "الولايات المتّحدة",
}