Ontology-based text summarization for business news articles

被引：0
|
作者：
Wu, CW [1 ]
Liu, CL [1 ]
机构：
[1] Natl Chengchi Univ, Dept Comp Sci, Taipei 11605, Taiwan
来源：
COMPUTERS AND THEIR APPLICATIONS | 2003年
关键词：
information retrieval; natural language processing; ontology application; text summarization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we compare two methods for article summarization. The first method is mainly based on term-frequency, while the second method is based on ontology. We build an ontology database for analyzing the main topics of the article. After identifying the main topics and determining their relative significance, we rank the paragraphs based on the relevance between main topics and each individual paragraph. Depending on the ranks, we choose desired proportion of paragraphs as summary. Experimental results indicate that both methods offer similar accuracy in their selections of the paragraphs.
引用
收藏
页码：389 / 392
页数：4
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