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Research on Semantic Text Mining Based on Domain Ontology

机译:基于领域本体的语义文本挖掘研究

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摘要

Text mining is an effective means of detecting potentially useful knowledge from large text documents. However conventional text mining technology cannot achieve high accuracy, because it cannot effectively make use of the semantic information of the text. Ontology provides theoretical basis and technical support for semantic information representation and organization. This paper improves the traditional text mining technology which cannot understand the text semantics. The author discusses the text mining methods based on domain ontology, and sets up domain ontology and database at first, then introduces the "concept-concept" correlation matrix and identifies the relationships of conceptions, and puts forward the text mining model based on domain ontology at last. Based on the semantic text mining model, the depth and accuracy of text mining is improved.
机译:文本挖掘是从大型文本文档中检测潜在有用知识的有效手段。然而,常规的文本挖掘技术不能实现高精度,因为它不能有效地利用文本的语义信息。本体为语义信息的表示和组织提供了理论基础和技术支持。本文对传统的无法理解文本语义的文本挖掘技术进行了改进。作者讨论了基于领域本体的文本挖掘方法,首先建立了领域本体和数据库,然后介绍了“概念—概念”相关矩阵,识别了概念之间的关系,提出了基于领域本体的文本挖掘模型。终于。基于语义文本挖掘模型,提高了文本挖掘的深度和准确性。

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