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Flexible KNN Algorithm for Text Categorization by Authorship Based on Features of Lingual Conceptual Expression

机译:基于语言概念表达特征的灵活的KNN作者文本分类算法

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Text categorization by authorship is useful in some applications and lingual conceptual expression is an effective expression to reduce the dimension of the VSM. In this application, we use KNN algorithm, which is a common, efficient and effective text categorization algorithm. In standard KNN algorithm, the K is fixed for different processing texts, and the weights for neighbors are equal. In this paper, a flexible KNN algorithm is combined with k-variable algorithm and weighting algorithm, which improves the effect of text categorization.
机译:按作者身份分类的文本在某些应用中很有用,而语言概念表达是减少VSM尺寸的有效表达。在此应用程序中,我们使用KNN算法,这是一种通用,高效且有效的文本分类算法。在标准的KNN算法中,对于不同的处理文本,K是固定的,而邻居的权重是相等的。本文将一种灵活的KNN算法与k变量算法和加权算法相结合,提高了文本分类的效果。

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