【作者】 杨丽鹏； 林世平；

【Author】 Yang LiPeng~1 Lin ShiPing~2 Department of Computer Science and Technology,Fuzhou University,Fuzhou 350002

【机构】 福州大学数学与计算机科学学院；

【摘要】 现有的大部分基于文本的本体学习方法对概念间非分类关系获取的研究都只停留在判断两个概念间是否存在关系的层次上,而无法为获取的关系赋予语义标签,得到的都是"匿名"关系。本文提出了一种基于关联规则和自然语言处理技术的从文本中获取概念间非分类关系的方法,为获得的关系赋予了相应的语义标签。实验表明,本文的方法能在一定程度上实现概念间非分类关系的自动获取。更多还原

【Abstract】 Within ontology learning from text,the existing methods for the extraction of non-taxonomic relations are mainly focus on deciding whether there are relations between two concepts,but could not label the extracted relations with semantic labels,so only get the anonymous relations.In this paper,we propose a non-taxonomic relation extraction method based on associations and natural language processing technologies,assigning semantic labels to the non-taxonomic relations learning from text.Experiments show that the method can to some extend automatic extracts the non-taxonomic relations between concepts.更多还原