Clustering web documents based on Multiclass spectral clustering

Xing He, Jiabing Wang, Zhong-Xian Zhang, Yi Cai
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引用次数: 4

Abstract

Multiclass spectral clustering is a clustering method which has been successfully applied in image segmentation and many other aspects. In this paper, Multiclass spectral clustering is used to cluster web documents including both English and Chinese pages. Through experiments, we found that Multiclass spectral clustering can be well used in web document clustering, and the method not only works well to cluster English web documents but also works well to cluster Chinese web documents clustering. We applied our method to a web search engine, and users can get the suitable results easily by just selecting the desirable classes.
基于多类谱聚类的web文档聚类
多类光谱聚类是一种成功应用于图像分割等多个方面的聚类方法。本文采用多类谱聚类方法对中英文网页文档进行聚类。通过实验,我们发现多类谱聚类可以很好地应用于web文档聚类,该方法不仅对英文web文档聚类效果良好,而且对中文web文档聚类效果也很好。将该方法应用到网络搜索引擎中,用户只需选择自己想要的类,就可以很容易地得到合适的搜索结果。
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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