Neural-based Chinese Idiom Recommendation for Enhancing Elegance in Essay Writing

Yuanchao Liu, Bo Pang, Bingquan Liu


Abstract
Although the proper use of idioms can enhance the elegance of writing, the active use of various expressions is a challenge because remembering idioms is difficult. In this study, we address the problem of idiom recommendation by leveraging a neural machine translation framework, in which we suppose that idioms are written with one pseudo target language. Two types of real-life datasets are collected to support this study. Experimental results show that the proposed approach achieves promising performance compared with other baseline methods.
Anthology ID:
P19-1552
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2019
Address:
Florence, Italy
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5522–5526
Language:
URL:
https://www.aclweb.org/anthology/P19-1552
DOI:
10.18653/v1/P19-1552
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/P19-1552.pdf