融合句子结构的抽象式文本摘要方法

传统序列到序列模型未充分利用输入文本的句子结构，导致其无法生成结构严谨、语法更好的摘要。因此，提出了一种融合句子基本结构的摘要生成方法。首先，明确提出融合句子结构生成文本摘要的概念。再者，在摘要生成器上增添了句子基本结构模块和监督模块，句子基本结构模块从输入文本中捕捉一系列句子结构，监督模块评估已捕获句子结构的重要性，以此协助句子基本结构模块从中提取可用的句子结构。最后，摘要生成器融合可用的句子结构生成最终摘要。在数据集LCSTS上的实验表明，此方法的ROUGE得分相较于seq2seq皆有提高，即其生成摘要的准确性优于seq2seq模型。实验也验证了句子基本结构模块和监督模块存在的必要性。

Abstractive text summary method based on sentence structure

Traditional seq2seq model didn''t fully utilize the sentence structure of the input text, this results in that seq2seq model can''t generate a text summary with rigorous structure and better grammar. Therefore, the paper proposed a summary generation method with basic structure of sentence. First of all, it explicitly proposed the concept of generating a text summary with sentence structure. Furthermore, it added a sentence structure module and a supervisor module on the summary generator. The sentence structure module captured a series of sentence structures from the input text, the supervisor module evaluated the importance of the sentence structures, this assisted the sentence structure module to capture some available sentence structures. Finally, the summary generator combined the available sentence structures to generate the final summary. The experiments on LCSTS show that its ROUGE scores are higher than seq2seq. In other words, its accuracy surpasses seq2seq. Experiments also verify the necessity of the existence of the sentence structure module and the supervisor module.