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首页> 外文期刊>International journal of computer science and network security >A Novel Fuzzy Based Clustering Algorithm for Text Classification
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A Novel Fuzzy Based Clustering Algorithm for Text Classification

机译:一种基于模糊的新型文本分类聚类算法

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摘要

Due to the flourish of World Wide Web and the rapid development of the Internet technology, the increasing volume of digital textual data become more and more unmanageable, therefore the importance of text classification has gained significant attention. Text classification pose some specific challenges such as high dimensionality with each document (data point) having only a very small subset of them and representing multiple labels at the same time. Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text classification. Many researchers worked on Feature Clustering for efficient text classification. Recently a Fuzzy based feature clustering was proposed in which Gaussian distribution is used for fuzzy membership function for clustering. But the problem of skewness may occur with this distribution. To overcome that we propose an efficient Fuzzy similarity based membership function for efficient clustering and with this proposed algorithm satisfactory results obtained.
机译:由于万维网的蓬勃发展和互联网技术的飞速发展,数字文本数据量的增加变得越来越难以管理,因此文本分类的重要性受到了广泛的关注。文本分类带来了一些特定的挑战,例如高维,每个文档(数据点)只有很小的一部分,并且同时表示多个标签。特征聚类是一种有效的方法,可以减少用于文本分类的特征向量的维数。许多研究人员致力于功能聚类以实现有效的文本分类。最近,提出了一种基于模糊的特征聚类,其中将高斯分布用于模糊隶属函数进行聚类。但是这种分布可能会出现偏斜问题。为了克服这个问题,我们提出了一种有效的基于模糊相似度的隶属度函数来进行有效的聚类,并且该算法能够获得令人满意的结果。

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