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Domain knowledge acquisition by automatic semantic annotating and pattern mining

机译:通过自动语义注释和模式挖掘获取领域知识

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摘要

Manual knowledge acquisition is extremely laborious and time consuming. In this paper, we propose a new automatic method for domain knowledge acquisition by semantic annotating and pattern mining. This method makes use of Minipar to label sentences and extract structural patterns. Semantic bank is proposed to annotate and represent concepts with semantic labels considering sentence context. The method can further learn and assign relations to previously extracted concepts by pattern matching. The involved concepts and semantic labels with learned relations together construct a domain knowledge base. Preliminary experiments on Yahoo! Data in “heart diseases” category show that this method is feasible for automatic domain knowledge acquisition.
机译:手动获取知识非常费力且费时。本文提出了一种通过语义注释和模式挖掘的自动获取领域知识的新方法。该方法利用Minipar标记句子并提取结构模式。提出了语义库,以考虑句子上下文的语义标签来注释和表示概念。该方法可以进一步通过模式匹配来学习关系并将其分配给先前提取的概念。所涉及的概念和带有学习关系的语义标签共同构成了一个领域知识库。 Yahoo!的初步实验“心脏病”类别中的数据表明,该方法对于自动领域知识获取是可行的。

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