المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
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الناشر: | جامعة الملك سعود |
المؤلف الرئيسي: | Al Kabi, Mohammed Naji (Author) |
مؤلفين آخرين: | Kazakzeh, Saif A. (Co-Author) , Al-Rababah, Saif A. (Co-Author) , Alsmadi, Izzat M. (Co-Author) , Abu Ata, Belal M. (Co-Author) |
المجلد/العدد: | مج27, ع2 |
محكمة: | نعم |
الدولة: |
السعودية |
التاريخ الميلادي: |
2015
|
الصفحات: | 94 - 103 |
DOI: |
10.33948/0584-027-002-001 |
ISSN: |
1319-1578 |
رقم MD: | 973535 |
نوع المحتوى: | بحوث ومقالات |
اللغة: | الإنجليزية |
قواعد المعلومات: | science |
مواضيع: | |
كلمات المؤلف المفتاحية: |
Natural Language Processing (NLP) | Computational Intelligence | Stemming | Information Retrieval
|
رابط المحتوى: |
المستخلص: |
Stemming algorithms are used in information retrieval systems, indexers, text mining, text classifiers etc., to extract stems or roots of different words, so that words derived from the same stem or root are grouped together. Many stemming algorithms were built in different natural languages. Khoja stemmer is one of the known and widely used Arabic stemmers. In this paper, we introduced a new light and heavy Arabic stemmer. This new stemmer is presented in this study and compared with two well-known Arabic stemmers. Results showed that accuracy of our stemmer is slightly better than the accuracy yielded by each one of those two well-known Arabic stemmers used for evaluation and comparison. Evaluation tests on our novel stemmer yield 75.03% accuracy, while the other two Arabic stemmers yield slightly lower accuracy. |
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ISSN: |
1319-1578 |