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Ontology Construction Based on Latent Topic Extraction in a Digital Library

机译:基于潜在主题提取的数字图书馆本体构建

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This paper discusses the automatic ontology construction process in a digital library. Traditional automatic ontology construction uses hierarchical clustering to group similar terms, and the result hierarchy is usually not satisfactory for human's recognition. Human-provided knowledge network presents strong semantic features, but this generation process is both labor-intensive and inconsistent under large scale scenario. The method proposed in this paper combines the statistical correction and latent topic extraction of textual data in a digital library, which produces a semantic-oriented and OWL-based ontology. The experimental document collection used here is the Chinese Recorder, which served as a link between the various missions that were part of the rise and heyday of the Western effort to Christianize the Far East. The ontology construction process is described and a final ontology in OWL format is shown in our result.
机译:本文讨论了数字图书馆中的自动本体构建过程。传统的自动本体构建使用层次聚类对相似的术语进行分组,结果层次通常不能令人满意。人类提供的知识网络具有很强的语义特征,但是在大规模的情况下,这一生成过程既劳动密集又不一致。本文提出的方法将统计校正和文本库中文本数据的潜在主题提取相结合,从而生成面向语义和基于OWL的本体。这里使用的实验性文件收集是“中国记录器”,它充当了各种任务之间的联系,这些任务是西方努力使远东基督教化的兴起和全盛时期的一部分。描述了本体的构建过程,并在我们的结果中显示了OWL格式的最终​​本体。

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