TSM。Web文档的选题方法

Myunggwon Hwang, Hyunjang Kong, Sunkyoung Baek, Pankoo Kim
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引用次数: 3

摘要

本文提出了一种针对Web文档的主题选择方法。我们的方法的思想是利用本体结构和每个术语的TF (term frequency)值。为了提高文档聚类的性能,迫切需要我们的研究。我们使用TF值和使用WordNet中定义的关系的术语之间的相关性值处理Web文档以获取关键字。然后,我们在选题过程中考虑了三种情况,提出了选题公式。总之,我们证明了我们的方法对于文档的主题选择非常有用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TSM. Topic Selection Method of Web Documents
In this paper, we propose a topic selection method about Web documents. The idea of our approach is to utilize an ontology structure and TF (term frequency) values of each term. For improving the performance of documents clustering, our research is strongly demanded. We process Web documents for keywords acquisition using TF values and relevancy values between terms using relations defined in WordNet. And then, we proposed the topic selection formula as we consider three kinds of cases during the topic selection. In conclusion, we demonstrate that our approach is very useful for the topic selection of documents
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