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In languages with high word inflation such as Arabic, stemming improves text retrieval performance by reducing words variants. We propose a change in the corpus-based stemming approach proposed by Xu and Croft for English and Spanish languages in order to stem Arabic words. We generate the conflation classes by clustering 3-gram representations of the words found in only 10% of the data in the first...
Arabic is a derivational language that provides invaluable features. Arabic roots are basic forms that are used to formulate words. They are limited sets that encapsulate the word’s linguistic features. The knowledge of roots’ frequencies is a valuable additional feature, especially when it is bound to a specific topic. This paper utilizes collision resulting from the stemming process where two or...
We use genetic algorithms and pattern matching to generate a morphological analyzer for Arabic verbs. Our approach consisted of developing general verb patterns and then applying these patterns to derive morphological rules. Except for some rare ambiguous cases, the resulting morphological analyzer is capable of recognizing all instances of verbs.
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