结合特色和深度学习的越南法律问答

Luu Hoai Linh, Nguyen Hai Long, Nguyen Hai Yen, Thi-Hai-Yen Vuong
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引用次数: 3

摘要

法律问题的回答是一个艰巨的问题,分为几个阶段,每个阶段都有自己的一套挑战。在这项工作中,我们通过提出组合特征(TF-IDF的余弦相似度,词嵌入的平均值;和Jaccard距离),并附有任务1的分类模型;集成学习任务2的多个深度学习模型。最后,我们为长文档采用了一种专门修改过的机制来完成任务3。这三种方法都取得了令人满意的结果,并有很大的改进潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vietnamese Legal Question Answering with combined features and deep learning
Legal Question Answering is an arduous problem that is divided into certain phases, each with its own set of challenges. In this work, we have accomplished three tasks given by the ALQAC 2021 competition, which are aimed at addressing the aforementioned problem, by proposing the combined features (cosine similarity of TF-IDF, an average of word embedding; and Jaccard distance) accompanied by a classification model for task 1; ensemble learning multiple deep learning models for task 2. Finally, we employed a specifically modified mechanism for long documents to undertake task 3. All three methods perform satisfactory results and have profuse potential improvements.
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