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Exploiting Conceptual Relations of Sentences for Multi-document Summarization

机译:利用句子的概念关系进行多文档摘要

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Multi-document Summarization becomes increasingly important in the age of big data. However, existing summarization systems do not or implicitly consider the conceptual relations of sentences. In this paper, we propose a novel method called Multi-document Summarization based on Explicit Semantics of Sentences (MDSES), which explicitly take conceptual relations of sentences into consideration. It is composed of three components: sentence-concept graph construction, concept clustering and summary generation. We first obtain sentence-concept semantic relation to construct a sentence-concept graph. Then we run graph weighting algorithm to get ranked weighted sentences and concepts. Besides, we obtain concept-concept semantic relation for concepts clustering to eliminate redundancy. Finally, we conduct summary generation to get informative summary. Experimental results on DUC dataset using ROUGE metrics demonstrate the good effectiveness of our methods.
机译:在大数据时代,多文档摘要变得越来越重要。但是,现有的摘要系统没有或暗中考虑句子的概念关系。在本文中,我们提出了一种基于显式语义(MDSES)的称为多文档摘要的新方法,该方法明确考虑了句子的概念关系。它由三个部分组成:句子概念图构造,概念聚类和摘要生成。我们首先获得句子概念语义关系,以构建句子概念图。然后我们运行图加权算法来获得排名加权的句子和概念。此外,我们获得了用于概念聚类的概念-概念语义关系,以消除冗余。最后,我们进行摘要生成以获取有用的摘要。使用ROUGE指标在DUC数据集上的实验结果证明了我们方法的良好有效性。

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