Research on Ontology-Based Text Clustering

Xiquan Yang, Dina Guo, XueYa Cao, JianYuan Zhou
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引用次数: 14

Abstract

Text clustering as a method of organizing retrieval results can organize large amounts of web search into a small number of clusters in order to facilitate users¿ quickly browsing. In this paper, we propose a text clustering method based on ontology which is different from traditional text clustering and can improve clustering results performance. This method implements word clustering by calculating word relativity and then implements text classification. Experiments show that the proposed method clustering trends to perform better than only single term frequency based method.
基于本体的文本聚类研究
文本聚类作为一种组织检索结果的方法,可以将大量的网络搜索组织成少量的聚类,以方便用户快速浏览。本文提出了一种不同于传统文本聚类的基于本体的文本聚类方法,提高了聚类结果的性能。该方法通过计算词相关性实现词聚类,进而实现文本分类。实验表明,该方法的聚类趋势优于仅基于单项频率的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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