融合句法指导与字符注意力机制的案情阅读理解方法

Case reading comprehension method combining syntactic guidance and character attention mechanism

案情阅读理解是机器阅读理解在司法领域的具体应用。案情阅读理解通过计算机阅读裁判文书,并回答相关问题,是司法智能化的重要应用之一。当前机器阅读理解的主流方法是采用深度学习模型对文本词语进行编码,并由此获得文本的向量表示。模型建立的核心问题是如何获得文本的语义表示,以及问题与上下文的匹配。考虑到句法信息有助于模型学习句子主干信息,以及中文字符具有潜在的语义信息,提出了融合句法指导与字符注意力机制的案情阅读理解方法。通过融合句法信息及中文字符信息,提升模型对案情文本的编码能力。在法研杯2019阅读理解数据集上的实验结果表明,所提出的方法与基线模型相比EM值提升了0.816,F1值提升了1.809%。

Case reading comprehension is the specific application of machine reading comprehension in judicial field.Case reading comprehension is one of the important applications of judicial intelligence,which reads the judgment documents by computer and answers the related questions.At present,the mainstream method of machine reading comprehension is to use deep learning model to encode the text words and obtain vector representation of the text.The core problem of model construction is how to obtain the semantic representation of the text and how to match the questions with the context.Considering that syntactic information is helpful for model learning the sentence skeleton information and Chinese characters have potential semantic information,a case reading comprehension method that integrates syntactic guidance and character attention mechanism was proposed.By fusing the syntactic information and Chinese character information,the coding ability of the model for the case text was improved.Experimental results on the reading comprehension dataset of Law Research Cup 2019 show that compared with the baseline model,the proposed method has the Exact Match(EM)value increased by 0.816 and the F1 value improved by 1.809%.