@inproceedings{daohuan-xuri-2023-contextualized,
title = "The Contextualized Representation of Collocation",
author = "Daohuan, Liu and
Xuri, Tang",
editor = "Sun, Maosong and
Qin, Bing and
Qiu, Xipeng and
Jiang, Jing and
Han, Xianpei",
booktitle = "Proceedings of the 22nd Chinese National Conference on Computational Linguistics",
month = aug,
year = "2023",
address = "Harbin, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2023.ccl-1.71",
pages = "836--846",
abstract = "{``}Collocate list and collocation network are two widely used representation methods of colloca-tions, but they have significant weaknesses in representing contextual information. To solve thisproblem, we propose a new representation method, namely the contextualized representation ofcollocate (CRC), which highlights the importance of the position of the collocates and pins acollocate as the interaction of two dimensions: association strength and co-occurrence position. With a full image of all the collocates surrounding the node word, CRC carries the contextualinformation and makes the representation more informative and intuitive. Through three casestudies, i.e., synonym distinction, image analysis, and efficiency in lexical use, we demonstratethe advantages of CRC in practical applications. CRC is also a new quantitative tool to measurelexical usage pattern similarities for corpus-based research. It can provide a new representationframework for language researchers and learners.{''}",
language = "English",
}
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<abstract>“Collocate list and collocation network are two widely used representation methods of colloca-tions, but they have significant weaknesses in representing contextual information. To solve thisproblem, we propose a new representation method, namely the contextualized representation ofcollocate (CRC), which highlights the importance of the position of the collocates and pins acollocate as the interaction of two dimensions: association strength and co-occurrence position. With a full image of all the collocates surrounding the node word, CRC carries the contextualinformation and makes the representation more informative and intuitive. Through three casestudies, i.e., synonym distinction, image analysis, and efficiency in lexical use, we demonstratethe advantages of CRC in practical applications. CRC is also a new quantitative tool to measurelexical usage pattern similarities for corpus-based research. It can provide a new representationframework for language researchers and learners.”</abstract>
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%0 Conference Proceedings
%T The Contextualized Representation of Collocation
%A Daohuan, Liu
%A Xuri, Tang
%Y Sun, Maosong
%Y Qin, Bing
%Y Qiu, Xipeng
%Y Jiang, Jing
%Y Han, Xianpei
%S Proceedings of the 22nd Chinese National Conference on Computational Linguistics
%D 2023
%8 August
%I Chinese Information Processing Society of China
%C Harbin, China
%G English
%F daohuan-xuri-2023-contextualized
%X “Collocate list and collocation network are two widely used representation methods of colloca-tions, but they have significant weaknesses in representing contextual information. To solve thisproblem, we propose a new representation method, namely the contextualized representation ofcollocate (CRC), which highlights the importance of the position of the collocates and pins acollocate as the interaction of two dimensions: association strength and co-occurrence position. With a full image of all the collocates surrounding the node word, CRC carries the contextualinformation and makes the representation more informative and intuitive. Through three casestudies, i.e., synonym distinction, image analysis, and efficiency in lexical use, we demonstratethe advantages of CRC in practical applications. CRC is also a new quantitative tool to measurelexical usage pattern similarities for corpus-based research. It can provide a new representationframework for language researchers and learners.”
%U https://aclanthology.org/2023.ccl-1.71
%P 836-846
Markdown (Informal)
[The Contextualized Representation of Collocation](https://aclanthology.org/2023.ccl-1.71) (Daohuan & Xuri, CCL 2023)
ACL
- Liu Daohuan and Tang Xuri. 2023. The Contextualized Representation of Collocation. In Proceedings of the 22nd Chinese National Conference on Computational Linguistics, pages 836–846, Harbin, China. Chinese Information Processing Society of China.