基于主题分割与PageRank算法的文本主题抽取

doi:10.11925/infotech.1003-3513.2010.12.06

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摘要

针对主题句抽取时完整性差的问题,在对文本进行主题分割的基础上,为每个主题包构建句子关系图,并采用基于图的PageRank算法对关系图中的句子排序,选取权重大的句子作为每个主题包的主题句。实验表明,该算法抽取的主题句对全文有很好的覆盖率。

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	段晓丽
	王宇

关键词 ：主题句抽取, 主题分割, 句子关系图, PageRank算法

Abstract：

Considering the completeness of subject extraction, this paper sorts the sentences with PageRank algorithm based on text theme divisions after reconstructing sentence relation map to every theme package. Then the sentence which has the maximum weight among all the texts is set to be the topics sentence. Experiments show that the topic sentence extraction algorithm has a good coverage of the full text.

Key words： Topic sentence extraction Subject segmenting Sentence relation map PageRank algorithm

收稿日期: 2010-11-10

TP391

基金资助:

本文系教育部人文社会科学项目“期刊文献知识元挖掘及知识仓库构建研究”(项目编号:09YJA870005)的研究成果之一。

引用本文:

段晓丽, 王宇. 基于主题分割与PageRank算法的文本主题抽取[J]. 现代图书情报技术, 2010, 26(12): 34-39.
Duan Xiaoli, Wang Yu. The Subject Extraction Based on Topic Segmentation and PageRank Algorithm. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2010.12.06.

链接本文:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2010.12.06

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