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Knowledge Graph and Deep Neural Network for Extractive Text Summarization by Utilizing Triples

机译:利用三元脉冲文本概述知识图和深神经网络

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In our research work, we represent the content of the sentence in graphical form after extracting triples from the sentences. In this paper, we will discuss novel methods to generate an extractive summary by scoring the triples. Our work has also touched upon sequence-to-sequence encoding of the content of the sentence, to classify it as a summary or a non-summary sentence. Our findings help to decide the nature of the sentences forming the summary and the length of the system generated summary as compared to the length of the reference summary.
机译:在我们的研究工作中,在从句子中提取三元组后,我们代表了图形形式中句子的内容。 在本文中,我们将讨论通过评分三元组来产生提取概要的新方法。 我们的工作还触及句子内容的顺序序列编码,将其作为摘要或非摘要句子进行分类。 与参考摘要的长度相比,我们的研究结果有助于决定形成概要的句子的性质和系统生成的摘要的长度。

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