基于知网和术语相关度的本体关系抽取研究

被引：7

作者：

傅继彬 ^{[1
]}

刘杰 ^{[2
]}

贾可亮 ^{[3
]}

毛金涛 ^{[1
]}

机构：

[1] 北京理工大学计算机科学技术学院

[2] 首都师范大学信息工程学院

[3] 山东经济学院信息管理学院

来源：

现代图书情报技术 | 2008年 / 09期

关键词：

关系抽取; 本体学习; 知网; 自然语言处理;

D O I：

暂无

中图分类号：

TP391.1 [文字信息处理];

学科分类号：

081203 ; 0835 ;

摘要：

提出一种基于知网和术语相关度的关系抽取方法。首先通过句法分析提取术语的上下文特征,结合自然语言特征和互信息的方法计算术语之间的相关度,然后使用术语的义原和动态角色作为关键词,在知网语义关系框架中定位关系,并为关系指定明确的语义标签。实验结果表明该方法具有较好的实用效果。

引用

页码：36 / 40

页数：5

共 9 条

[1]

Mathematical structures of language. Harris,Zelig S. . 1968

[2]

Learning Concept Hierarchies FromText Corpora Using Formal Concept Analysis. Cimiano P,Hotho A,Staab S. Journal of ArtificialIntelligence Research . 2005

[3]

RelExt:ATool for Relation Extraction fromText in Ontology Extension. Schutz A,Buitelaar P. Proceedings ofthe Internation-al Semantic Web Conference . 2005

[4]

Measures of Distributional Similarity. Lee L. Proceedingsofthe37th Annual Meeting ofthe Association forComputational Lin-guistics(ACL) . 1999

[5]

Automatic Acquisition of Hyponyms from Large TextCorpora. Hearst M A. Proceedings ofthe14th International Conferenceon Computational Linguistics(COLING) . 1992

[6]

Acquiring Conceptual Relationships from Domain-specific Texts. Yamaguchi T. Proceedings ofthe IJCAIWorkshopon Ontol-ogy Learning . 2001

[7]

Unsupervised learning of semantic relations between concepts of a molecular biology ontology. Massimiliano Ciramita,Ald Gangemi,and Esther Ratsch etc. Proceedings of the 19th International Joint Conference on Artificial Intelligence . 2005

[8]

A statistical corpus-based term extractor. PANTEL P,LIN D K. Proceedings of the 14th Biennial Conference of the Canadian So-ciety on Computational Studies of Intelligence:Advances in ArtificialIntelligence . 2001

[9]

Learning Relations usingCollocations. Heyer G,Lauter M,Quasthoff U,et al. Proceeding ofthe IJCAIWorkshopon Ontolo-gy Learning . 2001

← 1 →