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Towards CST-Enhanced Summarization

机译:迈向CST增强的总结

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摘要

In this paper, we propose to enhance the process of automatic extractive multi-document text summarization by taking into account cross-document structural relationships as posited in Cross-document Structure Theory (CST). An arbitrary multi-document extract can be CST-enhanced by replacing low-salience sentences with other sentences that increase the total number of CST relationships included in the summary. We show that CST-enhanced summaries outperform their unmodified counterparts using the relative utility evaluation metric. We also show that the effect of a CST relationship on an extract depends on its type.
机译:在本文中,我们建议通过考虑跨文档结构理论(CST)中提出的跨文档结构关系,来增强自动提取多文档文本摘要的过程。通过用其他句子代替低显着性句子,从而增加摘要中包括的CST关系总数,可以增强CST的任意多文档摘录。我们显示,使用相对效用评估指标,CST增强的摘要优于未修改的摘要。我们还表明,CST关系对提取物的影响取决于其类型。

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