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Applying the SOM model to text classification according to register and stylistic content

机译:根据寄存器和样式内容将SOM模型应用于文本分类

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摘要

We report on the application of the Self-Organizing Map (SOM) classification method to the task of categorizing texts according to their register and the style of their author. The SOM has been selected as its performance in various data-mining applications has been found to be highly successful. Here, the method is evaluated against the task of clustering textual data which are corpora of texts written in the Greek language; the parameters used depict linguistically important structural properties of the texts. The experiments reported indicate that the SOM results are equivalent to those generated by statistical methods.
机译:我们报告了自组织地图(SOM)分类方法在根据文本的注册和作者的样式对文本进行分类的任务中的应用。选择SOM是因为它在各种数据挖掘应用程序中的性能非常成功。在此,针对聚类文本数据的任务评估该方法,该文本数据是用希腊语编写的文本的语料库。使用的参数描述了文本在语言上的重要结构特性。报告的实验表明,SOM结果与通过统计方法生成的结果相同。

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