基于压缩的阿拉伯语文本分类

Haneen Ta'amneh, Ehsan Abu Keshek, M. B. Issa, M. Al-Ayyoub, Y. Jararweh
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引用次数: 16

摘要

文本分类(TC)是文本挖掘的基本问题之一。关于TC的研究有很多,方法有趣,结果也很好;然而,这些工作大多采用基于词的方法进行特征提取。在这项工作中,我们对另一种(基于字节或基于字符的)方法感兴趣,这种方法称为基于压缩的TC (CTC)。CTC已被用于一些语言,如英语和葡萄牙语,与基于单词的方法相比,它显示出一定的优点/缺点。这项工作将CTC应用于阿拉伯语,目的是调查阿拉伯语是否也存在这些优势/劣势。结果令人鼓舞,因为它们显示了将CTC用于阿拉伯语TC的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compression-based arabic text classification
Text classification (TC) is one of the fundamental problems in text mining. Plenty of works exist on TC with interesting approaches and excellent results; however, most of these works follow a word-based approach for feature extraction. In this work, we are interested in an alternative (byte-based or character-based) approach known as compression-based TC (CTC). CTC has been used for some languages such as English and Portuguese and it is shown to have certain advantages/ disadvantages compared with word-based approaches. This work applies CTC on the Arabic language with the purpose of investigating whether these advantages/disadvantages exists for the Arabic language as well. The results are encouraging as they show the viability of using CTC for Arabic TC.
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