A comparison of text‐classification techniques applied to Arabic text

Wiley - Tập 60 Số 9 - Trang 1836-1844 - 2009
Ghassan Kanaan1, Riyad Al‐Shalabi1, Sameh Ghwanmeh2, Hamda Al‐Ma'adeed1
1Arab Academy for Banking and Financial Services, Amman, Jordan
2Computer Engineering Department, Yarmouk University, Jordan

Tóm tắt

AbstractMany algorithms have been implemented for the problem of text classification. Most of the work in this area was carried out for English text. Very little research has been carried out on Arabic text. The nature of Arabic text is different than that of English text, and preprocessing of Arabic text is more challenging. This paper presents an implementation of three automatic text‐classification techniques for Arabic text. A corpus of 1445 Arabic text documents belonging to nine categories has been automatically classified using the kNN, Rocchio, and naïve Bayes algorithms. The research results reveal that Naïve Bayes was the best performer, followed by kNN and Rocchio.

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Wiley

Tập 60 Số 9

1836-1844

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