@inproceedings{abualhaija-etal-2017-metaheuristic,
title = "Metaheuristic Approaches to Lexical Substitution and Simplification",
author = "Abualhaija, Sallam and
Miller, Tristan and
Eckle-Kohler, Judith and
Gurevych, Iryna and
Zimmermann, Karl-Heinz",
editor = "Lapata, Mirella and
Blunsom, Phil and
Koller, Alexander",
booktitle = "Proceedings of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics: Volume 1, Long Papers",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/E17-1082",
pages = "870--880",
abstract = "In this paper, we propose using metaheuristics{---}in particular, simulated annealing and the new D-Bees algorithm{---}to solve word sense disambiguation as an optimization problem within a knowledge-based lexical substitution system. We are the first to perform such an extrinsic evaluation of metaheuristics, for which we use two standard lexical substitution datasets, one English and one German. We find that D-Bees has robust performance for both languages, and performs better than simulated annealing, though both achieve good results. Moreover, the D-Bees{--}based lexical substitution system outperforms state-of-the-art systems on several evaluation metrics. We also show that D-Bees achieves competitive performance in lexical simplification, a variant of lexical substitution.",
}
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<abstract>In this paper, we propose using metaheuristics—in particular, simulated annealing and the new D-Bees algorithm—to solve word sense disambiguation as an optimization problem within a knowledge-based lexical substitution system. We are the first to perform such an extrinsic evaluation of metaheuristics, for which we use two standard lexical substitution datasets, one English and one German. We find that D-Bees has robust performance for both languages, and performs better than simulated annealing, though both achieve good results. Moreover, the D-Bees–based lexical substitution system outperforms state-of-the-art systems on several evaluation metrics. We also show that D-Bees achieves competitive performance in lexical simplification, a variant of lexical substitution.</abstract>
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%0 Conference Proceedings
%T Metaheuristic Approaches to Lexical Substitution and Simplification
%A Abualhaija, Sallam
%A Miller, Tristan
%A Eckle-Kohler, Judith
%A Gurevych, Iryna
%A Zimmermann, Karl-Heinz
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F abualhaija-etal-2017-metaheuristic
%X In this paper, we propose using metaheuristics—in particular, simulated annealing and the new D-Bees algorithm—to solve word sense disambiguation as an optimization problem within a knowledge-based lexical substitution system. We are the first to perform such an extrinsic evaluation of metaheuristics, for which we use two standard lexical substitution datasets, one English and one German. We find that D-Bees has robust performance for both languages, and performs better than simulated annealing, though both achieve good results. Moreover, the D-Bees–based lexical substitution system outperforms state-of-the-art systems on several evaluation metrics. We also show that D-Bees achieves competitive performance in lexical simplification, a variant of lexical substitution.
%U https://aclanthology.org/E17-1082
%P 870-880
Markdown (Informal)
[Metaheuristic Approaches to Lexical Substitution and Simplification](https://aclanthology.org/E17-1082) (Abualhaija et al., EACL 2017)
ACL
- Sallam Abualhaija, Tristan Miller, Judith Eckle-Kohler, Iryna Gurevych, and Karl-Heinz Zimmermann. 2017. Metaheuristic Approaches to Lexical Substitution and Simplification. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 870–880, Valencia, Spain. Association for Computational Linguistics.