摘要
针对面向中文网络百科条目文章的属性和属性值抽取,提出一种无监督方法。此方法将属性值看做命名实体,利用频繁模式挖掘和关联分析,从文本中抽取类别属性;采用自扩展方法为属性建立触发词表;基于属性触发词和属性值实体标注挖掘属性值抽取模式,利用层次聚类算法获取高质量的模式。在互动百科中采集的数据集上进行实验,结果表明所提方法行之有效。
An unsupervised approach is proposed to extract attribute and attribute value from Chinese online encyclopedia entry articles. Attribute values are viewed as named entities and class attributes are extracted based on frequent patterns mining and association analysis. A bootstrapping method is used to find attribute trigger words for each attribute. Attribute value extraction patterns are generated automatically from sentences which contain attribute trigger words and named entity tags of attribute value. Hierarchy clustering algorithm is applied to obtain reliable patterns. Experimental dataset are collected from HudongBaike. The experiment results show that the method is feasible and effective.
出处
《北京大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第1期41-47,共7页
Acta Scientiarum Naturalium Universitatis Pekinensis
基金
国家自然科学基金(61170111
61202043
61262058)
中国科学院自动化研究所复杂系统管理与控制重点实验室开放课题(20110102)
中央高校基本科研业务费专项基金(SWJTU11ZT08)资助
关键词
知识获取
属性抽取
非结构化文本
模式挖掘
knowledge acquisition
attribute extraction
unstructured text
pattern mining
