Neural Network Enhances Writing Elegance through Chinese Idiom Recommendation

Neural Chinese Idiom Recommation for Enhancing Writing Elegance

In the pursuit of eloquent writing, the strategic incorporation of idioms can significantly enhance the sophistication and depth of a piece. However, the difficulty in memorizing an extensive repertoire poses a substantial obstacle to their effective utilization by writers. This paper introduces a novel approach that utilizes a neural translation framework for the problem of idiom recommation, imagining them as translations into pseudo target languages.

To substantiate this , two real-life datasets were meticulously collected and curated to support our research eavor. The experimental outcomes revealed that our proposed model outperforms alternative baseline methods with commable results, underscoring its efficacy in the realm of idiom recommation for writing enhancement.

The utilization of neural translation allows for an automatic identification and suggestion of idiomatic expressions based on their patterns and contexts within the text, bypassing the need for manual recall. This system simplifies by providing writers with a dynamic database of idioms that can be integrated into their work seamlessly.

In , our research not only advances the field of computational linguistics but also provides practical assistance to those ming to enrich their written communication with culturally nuanced expressions. The implementation of such a neural-based idiom recommation system could potentially revolutionize the way authors compose texts, promoting more elegant and sophisticated s while reducing the cognitive load associated with memorization.

Citation:

Liu, Y., Pang, B., Liu, B. 2019. Neural-Based Chinese Idiom Recommation for Enhancing Elegance in Essay Writing. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5522-5526, Florence, Italy. doi:10.18653v1P19-1552

This work was supported by list any supporting institutions or grants if applicable.

The revised version incorporates more formal tone and structure typically expected in academic writing. It also includes a bibliography-style citation format which should be used when referencing the paper in an academic context.

Translation of the reference text assuming the above is not needed:

In pursuit of enhancing eloquence through sophisticated , idioms play a crucial role by adding depth and richness to written communication. However, their effective integration poses challenges due to the demanding task of memorization. This paper proposes an innovative solution employing neural translation techniques for idiom recommation, conceptualizing them as translations into hypothetical target languages.

Two comprehensive datasets were meticulously compiled to ground our research eavor. The empirical findings demonstrated that our model surpasses other baseline methods with notable performance gns, emphasizing its efficacy in the context of enhancing idiomatic use.

The application of neural translation enables automatic detection and suggestion of idioms based on their syntactic patterns and contextual relevance within texts, thereby alleviating the cognitive burden of manual recall. This system streamlines the by providing authors with a dynamic repository of idio be seamlessly integrated into their compositions.

Conclusively, this study not only advances computational linguistics but also offers practical d for authors ming to craft more elegant and sophisticated works through culturally enriched expressions. The implementation of such an idiom recommation system via neural means could potentially transform the by facilitating more nuanced linguistic use while mitigating the cognitive strn associated with memorization.

Citation:

Liu, Y., Pang, B., Liu, B. 2019. Neural-Based Chinese Idiom Recommation for Enhancing Elegance in Essay Writing. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5522-5526, Florence, Italy. doi:10.18653v1P19-1552
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