Doaa Samy

Jabalín: A Comprehensive Computational Model of Modern Standard Arabic Verbal Morphology Based on Traditional Arabic Prosody

The computational handling of Modern Standard Arabic is a challenge in the field of natural language processing due to its highly rich morphology. However, several authors have pointed out that the Arabic morphological system is in fact extremely regular. The existing Arabic morphological analyzers have exploited this regularity to variable extent, yet we believe there is still some scope for improvement. Taking inspiration in traditional Arabic prosody, we have designed and implemented a compact and simple morphological system which in our opinion takes further advantage of the regularities encountered in the Arabic morphological system. The output of the system is a large-scale lexicon of inflected forms that has subsequently been used to create an Online Interface for a morphological analyzer of Arabic verbs. The Jabalin Online Interface is available at http://elvira.lllf.uam.es/jabalin/, hosted at the LLI-UAM lab. The generation system is also available under a GNU GPL 3 license.

A preliminary approach to recognize generic drug names by combining UMLS resources and USAN naming conventions

This paper presents a system for drug name identification and classification in biomedical texts.

Detecting semantic relations between nominals using support vector machines and linguistic-based rules

This paper describes the improvement of an automatic system for detecting semantic relations between nominals by the use of linguistically motivated knowledge combined with machine learning techniques. A previous version of the system using a Support Vector Machine classifier was evaluated in the 4th International Workshop on Semantic Evaluations, SEMEVAL [5]. The performance of the system improved significantly by the application of the linguistic based rules.