A comparison of text-classification techniques applied to Arabic text.
Many 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 i...
| Publicado en: | Journal of the American Society for Information Science & Technology Vol. 60; no. 9; pp. 1836 - 1845 |
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| Autores principales: | , , , |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Sep2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105418487&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105418487 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15322882 IGD jtl: Journal of the American Society for Information Science & Technology issn: 15322882 maglogo: Y pubinfo: dt: Sep2009 vid: 60 iid: 9 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 105418487 2010385967 10.1002/asi.20832 105418487 ppf: 1836 ppct: 9 formats: tig: atl: A comparison of text-classification techniques applied to Arabic text. aug: au: Kanaan G Al-Shalabi R Ghwanmeh S Al-Ma'adeed H affil: Arab Academy for Banking and Financial Services, Amman, Jordan sug: subj: Algorithms Utilization Arabs Classification Methods Language Natural Language Processing Human ab: Many 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. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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