基于BERT的唐诗典故自动识别

Xuemei Tang, Shichen Liang, Jianyu Zheng, Renfen Hu, Zhiying Liu
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引用次数: 2

摘要

本文提出了一种自动识别唐诗典故的方法。文本的表示由The SiKuQuanShu预训练的BERT进行训练。前20个候选典故与原句的语义相似度最高。然后通过基于规则的排序算法更新候选典故的排序。在最终的实验结果中,与最终排名top - 1相同的正确典故的精度达到63.74%,最终排名TOP-3的正确典故出现的精度达到70.66%,最终排名TOP-5的正确典故出现的精度达到74.82%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Recognition of Allusions in Tang Poetry Based on BERT
In this paper, we propose an automated method for recognize allusions in Tang poetry. The representation of text is trained by BERT pre-trained by The SiKuQuanShu. The TOP-20 candidate allusions have the highest semantic similarity to the original sentence. Then update the ranking of candidate allusions by rule-based ranking algorithm. In the final experimental results, the precision of the correct allusion same as the final ranking TOP-I reached 63.74%, the precision of the correct allusion appears in the final ranking TOP-3 reached 70.66%, and the precision of the correct allusion appears in the final ranking TOP-5 reached 74.82%.
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