关键词: 知识获取, 属性抽取, 非结构化文本, 模式挖掘

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