Anas Youssef Boubas

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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.
There have been many developments in content-based image retrieval (CBIR) recently. While retrieval quality of such systems has improved dramatically in the last decade, the complexities involved made most available systems impractical in real-life use. These complexities are a combination of space use and computational time required. Most approaches(More)
Firstly we covered the problem of rule definition for x-fixing Arabic roots. Instead of the traditional approach that relies on the semantics conveyed by x-fixing, we based our approach on the lexica. Presented in this paper an extensible schema for rules definition, which we used to partially cover the cases of verbs produced by preand suffixing triliteral(More)
Image abstraction has wide spectrum of application, especially for computationally intensive application such as content-based image retrieval (CBIR). A recently developed abstraction system was demonstrated to enhance the performance of CBIR systems while reducing the space and time complexities. The system is based on Singular Value Decomposition (SVD), a(More)
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