Neural Network Approach to Enhancing Chinese Essay Elegance via Idiom Recommendation

Neural-based Chinese Idiom Recommation System for Enhancing Literary Elegance in Writing

By Yuanchao Liu, Bo Pang, and Bingquan Liu

Abstract:

Enhancing the eloquence of written language through idiomatic expressions poses a significant challenge due to their complexity and difficulty in memorization. This paper tackles the issue of idioms recommation by adopting a neural translation framework, presuming that idiom applications are translated into a pseudo target language for clarity. We gather two types of real-life datasets to support this study's objectives. Experimental outcomes demonstrate our proposed approach surpasses conventional baseline methods in performance.

Introduction:

In Chinese essay writing, the strategic use of idioms can significantly enhance the elegance and impact of the text. However, mastering these expressions requires extensive learning and memorization, a barrier that often hinders their effective integration into written content. To address this challenge, we propose a neural-based system designed to recomm appropriate idiomatic usage based on contextual analysis.

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Our solution involves constructing a neural translation NMT framework where each idiom is treated as being translated from the source language to a pseudo target language specifically designed for clarity and ease of understanding. We collect two distinct real-life datasets: one for trning purposes and another for validation and testing to ensure our model's efficacy.

Results:

Experiments conducted on these datasets showcase that our neural-based idiom recommation system outperforms existing methods in terms of accuracy, demonstrating its potential as a valuable tool for enhancing literary eloquence through idiomatic expressions. s highlight the system's capability to identify suitable idioms based on context and relevance, thereby ding authors in effectively incorporating them into their writing.

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In , our neural-based Chinese idiom recommation system represents a significant advancement in assisting writers in leveraging idio enrich their prose. By streamlining of identifying appropriate expressions through techniques, we m to facilitate more elegant and impactful written communication in essays and beyond.

Acknowledgements:

We ext our gratitude to all contributors who provided datasets for this study and to the Association for Computational Linguistics ACL for supporting the 57th Annual Meeting where this research was presented. Their contributions have been instrumental in advancing our understanding of idiomatic use in Chinese writing.

References:

• Liu, Y., Pang, B., Liu, B. 2019. Neural-based Chinese Idiom Recommation for Enhancing Elegance in Essay Writing. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, July, pp. 5522-5526.

Ethics Statement:

This research was conducted with full compliance to ethical standards set by ACL and adhered to guidelines for data privacy and confidentiality, ensuring responsible use of information collected for trning and validation purposes.

Citation Format:

Liu, Y., Pang, B., Liu, B. 2019. Neural-based Chinese Idiom Recommation System for Enhancing Literary Elegance in Writing. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, July.

URL: ACL Anthologyhttps:aclanthology.orgP19-1552

DOI: 10.18653v1P19-1552
This article is reproduced from: https://aclanthology.org/P19-1552

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