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Sentence Extraction by Graph Neural Networks

机译:通过图形神经网络提取句子

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In this paper, we will apply a recently proposed connection-ist model, namely, the Graph Neural Network, for processing the graph formed by considering each sentence in a document as a node and the relationship between two sentences as an edge. Using commonly accepted evaluation protocols, the ROGUE toolkit, the technique was applied to two text summarization benchmarks, namely DUC-2001 and DUC-2002 respectively. It is found that the results obtained are comparable to the best results achieved using other techniques.
机译:在本文中,我们将应用最近提出的连接IST模型,即图形神经网络,用于处理通过将文档中的每个句子视为节点的每个句子以及作为边缘的两个句子之间的关系而形成的图表。使用常见的评估协议,Rogue Toolkit,该技术分别应用于两个文本摘要基准,即DUC-2001和Duc-2002。发现获得的结果与使用其他技术实现的最佳结果相当。

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