Improving stemming for Arabic information retrieval: light stemming and co-occurrence analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Quantitative evaluation of passage retrieval algorithms for question answering
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Rapid customization of an information extraction system for a surprise language
ACM Transactions on Asian Language Information Processing (TALIP)
A computational analysis of complex noun phrases in Navy messages
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Arabic finite-state morphological analysis and generation
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Machine transliteration of names in Arabic text
SEMITIC '02 Proceedings of the ACL-02 workshop on Computational approaches to semitic languages
Building a shallow Arabic Morphological Analyzer in one day
SEMITIC '02 Proceedings of the ACL-02 workshop on Computational approaches to semitic languages
TAGARAB: a fast, accurate Arabic name recognizer using high-precision morphological analysis
Semitic '98 Proceedings of the Workshop on Computational Approaches to Semitic Languages
Arabic to French sentence alignment: exploration of a cross-language information retrieval approach
Semitic '07 Proceedings of the 2007 Workshop on Computational Approaches to Semitic Languages: Common Issues and Resources
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The goal of many natural language processing platforms is to be able to someday correctly treat all languages. Each new language, especially one from a new language family, provokes some modification and design changes. Here we present the changes that we had to introduce into our platform designed for European languages in order to handle a Semitic language. Treatment of Arabic was successfully integrated into our cross language information retrieval system, which is visible online.