An Algorithm of Web Text Clustering Analysis Based on Fuzzy Set

Yun Peng, S. Ding
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Abstract

There are a large quantity of non-certain and non-structure contents in the Web text at the present time. It is difficult to cluster the text by some normal classification methods. An algorithm of Web text clustering analysis based on fuzzy set is proposed in this paper, and the algorithm has been described in detail by example. The technique can improve the algorithm complexity of time and space, increase the robustness of the algorithm. To check the accuracy and efficiency of the algorithm, the comparative analysis of the sample and test data is provided in the end.
基于模糊集的Web文本聚类分析算法
目前,网络文本中存在着大量的非确定性、非结构性内容。常规的分类方法很难对文本进行聚类。本文提出了一种基于模糊集的Web文本聚类分析算法,并通过实例对该算法进行了详细说明。该技术可以提高算法的时间复杂度和空间复杂度,增强算法的鲁棒性。为了验证算法的准确性和效率,最后给出了样本和测试数据的对比分析。
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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