@inproceedings{rigouts-terryn-2023-supervised,
title = "Supervised Feature-based Classification Approach to Bilingual Lexicon Induction from Specialised Comparable Corpora",
author = "Rigouts Terryn, Ayla",
editor = "Haddad, Amal Haddad and
Terryn, Ayla Rigouts and
Mitkov, Ruslan and
Rapp, Reinhard and
Zweigenbaum, Pierre and
Sharoff, Serge",
booktitle = "Proceedings of the Workshop on Computational Terminology in NLP and Translation Studies (ConTeNTS) Incorporating the 16th Workshop on Building and Using Comparable Corpora (BUCC)",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.contents-1.8",
pages = "59--68",
abstract = "This study, submitted to the BUCC2023 shared task on bilingual term alignment in comparable specialised corpora, introduces a supervised, feature-based classification approach. The approach employs both static cross-lingual embeddings and contextual multilingual embeddings, combined with surface-level indicators such as Levenshtein distance and term length, as well as linguistic information. Results exhibit improved performance over previous methodologies, illustrating the merit of integrating diverse features. However, the error analysis also reveals remaining challenges.",
}
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%0 Conference Proceedings
%T Supervised Feature-based Classification Approach to Bilingual Lexicon Induction from Specialised Comparable Corpora
%A Rigouts Terryn, Ayla
%Y Haddad, Amal Haddad
%Y Terryn, Ayla Rigouts
%Y Mitkov, Ruslan
%Y Rapp, Reinhard
%Y Zweigenbaum, Pierre
%Y Sharoff, Serge
%S Proceedings of the Workshop on Computational Terminology in NLP and Translation Studies (ConTeNTS) Incorporating the 16th Workshop on Building and Using Comparable Corpora (BUCC)
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F rigouts-terryn-2023-supervised
%X This study, submitted to the BUCC2023 shared task on bilingual term alignment in comparable specialised corpora, introduces a supervised, feature-based classification approach. The approach employs both static cross-lingual embeddings and contextual multilingual embeddings, combined with surface-level indicators such as Levenshtein distance and term length, as well as linguistic information. Results exhibit improved performance over previous methodologies, illustrating the merit of integrating diverse features. However, the error analysis also reveals remaining challenges.
%U https://aclanthology.org/2023.contents-1.8
%P 59-68
Markdown (Informal)
[Supervised Feature-based Classification Approach to Bilingual Lexicon Induction from Specialised Comparable Corpora](https://aclanthology.org/2023.contents-1.8) (Rigouts Terryn, ConTeNTS-WS 2023)
ACL