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An automatic acquisition of domain knowledge from list-structrued text in Baidu encyclopedia

机译:从百度百科的列表结构文本中自动获取领域知识

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We propose a novel method which can automatically extract new concepts and semantic relations between concepts, in order to support the domain ontology evolvement. We collect the corpus from a free Chinese encyclopedia called Baidu encyclopedia, which is similar to Wikipedia. We locate lists from the Baidu encyclopedia, and extract domain knowledge from the lists. Further more, we use a knowledge assessor to ensure the validity of extracted knowledge. In the experiments, we make a practical attempt to evolve the Chinese Law Ontology (CLO V0), and show that our method can improve the completeness and coverage of CLO V0.
机译:为了支持领域本体的发展,我们提出了一种新颖的方法,该方法可以自动提取新概念以及概念之间的语义关系。我们从免费的中国百科全书(称为百度百科)中收集语料库,该百科全书与维基百科类似。我们从百度百科全书中找到列表,并从列表中提取领域知识。此外,我们使用知识评估器来确保提取的知识的有效性。在实验中,我们进行了实践尝试以发展中国法律本体论(CLO V0),并表明我们的方法可以提高CLO V0的完整性和覆盖率。

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