Abstract: 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.

Key words: knowledge acquisition, attribute extraction, unstructured text, pattern mining

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。

关键词: 知识获取, 属性抽取, 非结构化文本, 模式挖掘