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Sentence Ordering for Coherent Multi-document Summary Generation

机译:连贯多文档摘要生成的句子排序

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Web queries often give rise to a lot of documents and the user is overwhelmed by the information. Query-specific extractive summarization of a selected set of retrieved documents helps the user to get a gist of the information. The current extractive summary generation systems focus on extracting query-relevant sentences from the documents. However, the selected sentences are presented either in the order in which the documents were considered or in the order in which they were selected. This approach does not guarantee a coherent summary. In this paper, we propose incremental integrated graph to represent the sentences in a collection of documents. Sentences from the documents are merged into a master sequence to improve coherence and flow. The same ordering is used for sequencing the sentences in the extracted summary. User evaluations indicate that the proposed technique markedly improves the user satisfaction with regard to coherence in the summary.
机译:Web查询通常会产生大量文档,并且用户不知所措。选择的一组检索文档的特定于查询的提取摘要可帮助用户了解信息的要点。当前的提取摘要生成系统专注于从文档中提取与查询相关的句子。但是,所选句子以考虑文档的顺序或选择文档的顺序显示。这种方法不能保证摘要的连贯性。在本文中,我们提出了增量集成图来表示文档集中的句子。来自文档的句子被合并到主序列中,以提高连贯性和流程性。使用相同的顺序对提取的摘要中的句子进行排序。用户评估表明,所提出的技术在摘要中的一致性方面显着提高了用户满意度。

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