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Multi-document summarization using sentence clustering

机译:使用句子群集的多文件摘要

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This paper presents an approach to query focused multi document summarization by combining single document summary using sentence clustering. Both syntactic and semantic similarity between sentences is used for clustering. Single document summary is generated using document feature, sentence reference index feature, location feature and concept similarity feature. Sentences from single document summaries are clustered and top most sentences from each cluster are used for creating multi-document summary. We observed an average F-measure of 0.33774 on DUC 2002 multi-document dataset, which is comparable to three best performing systems reported on the same dataset.
机译:本文通过使用句子群集结合单个文档摘要,介绍了一种查询聚焦多文件摘要的方法。 句子之间的句法和语义相似性都用于聚类。 使用文档功能,句子引用索引功能,位置特征和概念相似性功能生成单个文档摘要。 单个文件摘要的句子是群集的,每个群集的大多数句子都用于创建多文档摘要。 我们在DUC 2002多文档数据集中观察了0.33774的平均F测量值,这与同一数据集上报告的三个最佳执行系统相当。

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