New graph-based text summarization method

S. alZahir, Qandeel Fatima, M. Cenek
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引用次数: 10

Abstract

The exponential growth of text data on the World Wide Web as well as on databases off line created a critical need for efficient text summarizers that significantly reduce its size while maintaining its integrity. In this paper, we present a new multigraph-based text summarizer method. This method is unique in that it produces a multi-edge-irregular-graph that represents words occurrence in the sentences of the target text. This graph is then converted into a symmetric matrix from which we can produce the ranking of sentences and hence obtain the summarized text using a threshold. To test our method performance, we compared our results with those from the most popular publicly available text summarization software using a corpus of 1000 samples from 6 different applications: health, literature, politics, religion, science and sports. The simulation results show that the proposed method produced better or comparable summaries in all cases. The proposed method is fast and can be implement for real time summarization.
新的基于图的文本摘要方法
万维网上的文本数据以及离线数据库上的文本数据呈指数级增长,因此迫切需要高效的文本摘要器,以便在保持其完整性的同时显著减小其大小。本文提出了一种新的基于多图的文本摘要器方法。这种方法的独特之处在于它产生一个多边不规则图,表示目标文本句子中出现的单词。然后将这个图转换为一个对称矩阵,我们可以从中生成句子的排名,从而使用阈值获得摘要文本。为了测试我们的方法的性能,我们将我们的结果与来自最流行的公开文本摘要软件的结果进行了比较,使用了来自6个不同应用程序的1000个样本的语料库:健康、文学、政治、宗教、科学和体育。仿真结果表明,所提出的方法在所有情况下都能产生更好或可比较的摘要。该方法速度快,可实现实时摘要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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