@conference { ISI:000376431400014, title = {A Lightweight System for Correction of Arabic Derived Words}, booktitle = {PROCEEDINGS OF THE MEDITERRANEAN CONFERENCE ON INFORMATION \& COMMUNICATION TECHNOLOGIES 2015, VOL 1}, series = {Lecture Notes in Electrical Engineering}, volume = {380}, year = {2016}, note = {Mediterranean Conference on Information and Communication Technologies (MedCT), MOROCCO, MAY 07-09, 2015}, pages = {131-138}, abstract = {In this paper, we address the lexicon insufficient problem used in the automatic spell checker. In order to solve that deficiency, we developed an approach that aims to correct the derived words, considering that the most Arabic words are derived ones by adjusting the Levenshtein algorithm to our need. This method is based on a corpus constituted of surface patterns and roots characterized by a scaled down size compared to conventional approaches The proposed method reduced the execution time while maintaining the highest correction rate.}, isbn = {978-3-319-30301-7; 978-3-319-30299-7}, issn = {1876-1100}, doi = {10.1007/978-3-319-30301-7\_14}, author = {Nejja, Mohammed and Yousfi, Abdellah}, editor = {ElOualkadi, A and Choubani, F and ElMoussati, A} } @conference { ISI:000373736100013, title = {The context in automatic spell correction}, booktitle = {INTERNATIONAL CONFERENCE ON ADVANCED WIRELESS INFORMATION AND COMMUNICATION TECHNOLOGIES (AWICT 2015)}, series = {Procedia Computer Science}, volume = {73}, year = {2015}, note = {International Conference on Advanced Wireless Information and Communication Technologies (AWICT), Natl Sch Engineers Sousse, TUNISIA, OCT 05-07, 2015}, pages = {109-114}, abstract = {Automatic spell checker systems aim to verify and correct erroneous words through a suggested set of words that are the nearest lexically to the erroneous ones. However, the main disadvantage of those systems is that the wanted solution may bethe most distant lexically but the most appropriate in context. To correctly sort these solutions, the corrector must have some information about the general context of the text; the paragraph or the neighboring words of the misspelled word. In this paper, we will present an automatic spell checking method according to the context. This method is based on a learning corpus containing a distribution of the appearance probability of a word in different contexts. It combines the lexical correction via the Levenstein algorithm and the context based correction through a well definedlearning corpus which is composed of documents collected from the internet. This approach has proven efficiency and the obtained results are much more improved and satisfactory.}, issn = {1877-0509}, doi = {10.1016/j.procs.2015.12.055}, author = {Nejja, Mohammed and Yousfi, Abdellah}, editor = {Boubiche, DE and Hidoussi, F and Cruz, HT} }