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Improving Document Classification Effectiveness Using Knowledge Exploited by Ontologies

机译:利用本体开发的知识提高文档分类效率

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In this paper, we propose a new document classification model which utilizes background knowledge gathered by ontologies for document representation. A document is represented using a set of ontology concepts that are acquired by exact matching technique and through identification and extraction of new terms which can be semantically related to these concepts. In addition, a new concept weighting scheme composed of concept relevance and importance is employed by the model to compute weight of concepts. We conducted experiments to test the model and the obtained results showed that a considerable improvement of classification performance is achieved by using our proposed model.
机译:在本文中,我们提出了一种新的文档分类模型,该模型利用本体收集的背景知识进行文档表示。使用一组本体概念来表示文档,这些本体概念是通过精确匹配技术以及通过识别和提取与这些概念在语义上相关的新术语而获得的。此外,该模型采用了一种由概念相关性和重要性组成的新概念加权方案,以计算概念的权重。我们进行了实验以测试模型,获得的结果表明,使用我们提出的模型可以显着提高分类性能。

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