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http://hdl.handle.net/20.500.12358/23860
TitleArabic Text Classification Using Maximum Entropy
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Abstract

In organizations, a large amount of information exists in text documents. Therefore, it is important to use text mining to discover knowledge from these unstructured data. Automatic text classification considered as one of important applications in text mining. It is the process of assigning a text document to one or more predefined categories based on their content. This paper focus on classifying Arabic text documents. Arabic language is highly inflectional and derivational language which makes text mining a complex task. In our approach, we first preprocessed data using natural language processing techniques such as tokenizing, stemming and part-of-speech. Then, we used maximum entropy method to classify Arabic documents. We experimented our approach using real data, then we compared the results with other existing systems.

Authors
El-Halees, Alaa M.
TypeJournal Article
Date2007
LanguageEnglish
Subjects
maximum entropy
text data mining
automatic documents classification
arabic natural language processing
Published inIUG Journal for Natural and Engineering Studies
SeriesVolume: 15, Number: 1
Publisherالجامعة الإسلامية - غزة
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  • Staff Publications- Faculty of Information Technology [192]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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