Keyphrase extraction from Chinese news web pages based on semantic relations

被引：0

作者：

Xie, Fei ^{[1
,4
]}

Wu, Xindong ^{[1
,2
]}

Hu, Xue-Gang ^{[1
]}

Wang, Fei-Yue ^{[3
]}

机构：

[1] School of Computer Science and Information Engineering, Hefei University of Technology, Heifei,230009, China

[2] Department of Computer Science, University of Vermont, Burlington,VT,50405, United States

[3] Institute of Automation, Chinese Academy of Sciences, Beijing, China

[4] Department of Computer Science and Technology, Hefei Teachers College, Hefei,230061, China

来源：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2008年 / 5075卷

关键词：

Extraction; -; Chains; Semantics;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Keyphrases are very useful for saving time on browsing through the news web pages. A new keyphrase extraction method from Chinese news web pages based on semantic relations is presented in this paper. Semantic relations between phrases are analyzed, and a lexical chain is used to construct a semantic relation graph. Keyphrases are extracted and a semantic link graph is built on the lexical chains. News web pages with core hints are selected from www.163.com to test our method. The experimental results show that the proposed method substantially outperforms the method based on term frequency, especially when the number of keyphrases extracted is 3 – the precision is improved by 26.97 percent, and the recall is improved by 20.93 percent. © Springer-Verlag Berlin Heidelberg 2008.

引用

页码：490 / 495