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首页> 外文会议>2nd Workshop on Argumentation mining 2015 >Learning Sentence Ordering for Opinion Generation of Debate
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Learning Sentence Ordering for Opinion Generation of Debate

机译：学习句子排序以产生辩论意见

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摘要

We propose a sentence ordering method to help compose persuasive opinions for debating. In debate texts, support of an opinion such as evidence and reason typically follows the main claim. We focused on this claim-support structure to order sentences, and developed a two-step method. First, we select from among candidate sentences a first sentence that is likely to be a claim. Second, we order the remaining sentences by using a ranking-based method. We tested the effectiveness of the proposed method by comparing it with a general-purpose method of sentence ordering and found through experiment that it improves the accuracy of first sentence selection by about 19 percentage points and had a superior performance over all metrics. We also applied the proposed method to a constructive speech generation task.
机译：我们提出一种句子排序方法，以帮助撰写有说服力的辩论意见。在辩论文本中，主要主张是证据和理由等观点的支持。我们将重点放在此请求支持结构上以对句子进行排序，并开发了一种两步方法。首先，我们从候选句子中选择可能是主张的第一句。其次，我们使用基于排名的方法对其余句子进行排序。通过与通用的句子排序方法进行比较，我们测试了该方法的有效性，并通过实验发现，该方法将第一句选择的准确性提高了约19个百分点，并且在所有指标上均具有出色的性能。我们还将提出的方法应用于建设性的语音生成任务。

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