基于段落-句子互增强的自动文摘算法

计算机科学 ›› 2013, Vol. 40 ›› Issue (Z11): 246-250.

基于段落-句子互增强的自动文摘算法

谢浩,孙伟

中山大学信息科学与技术学院广州510006;中山大学软件学院广州510006

出版日期:2018-11-16 发布日期:2018-11-16

Paragraph-Sentence Mutual Reinforcement Based Automatic Summarization Algorithm

XIE Hao and SUN Wei

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 句子排序问题是文本自动摘要的核心问题,基于互增强关系(MRP)的基本思想,提出一种新的句子排序模型——段落-句子互增强模型。利用段落关系,通过段落句子的互增强,迭代计算出句子的显著度,抽取出文摘句。分析了模型中的内、外影响因子对算法效果的影响并对冗余处理进行了讨论。实验表明,将其运用在单文本自动摘要中,能取得高质量的文摘。

关键词: 句子排序,互增强关系,自动文摘

Abstract: Sentence ranking is the key issue of text automatic summarization．Based on mutual reinforcement principles,we proposed a new sentence ranking model——paragraph-sentence mutual reinforcement model．With the relation between paragraphs and the mutual reinforcement between paragraphs and sentences,it iteratively computes the salience of the sentences and extract the summary sentences．We analyzed the effect of the internal and external reinforced factor and discussed the problem of redundancy remove．Experiments show that it can extract high quality summary when it applies to the single-document summarization.

Key words: Sentence ranking,Mutual reinforcement principle,Automatic summarization

谢浩,孙伟. 基于段落-句子互增强的自动文摘算法[J]. 计算机科学, 2013, 40(Z11): 246-250. https://doi.org/

XIE Hao and SUN Wei. Paragraph-Sentence Mutual Reinforcement Based Automatic Summarization Algorithm[J]. Computer Science, 2013, 40(Z11): 246-250. https://doi.org/

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