Titlebook: Arabic Language Processing: From Theory to Practice; 6th International Co Abdelmonaime Lachkar,Karim Bouzoubaa,Abdelhak Lekh Conference pro

爆炸

元音

Empirical Evaluation of Word Representations on Arabic Sentiment Analysisdatasets: ASTD and SemEval 2017 datasets. We explore the importance of various unsupervised word representations learned from unannotated corpora. Experimental results showed that we were able to outperform the previous state-of-the-art systems on the datasets without using any kind of hand engineering features.

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浮雕

Automatic Identification of Moroccan Colloquial Arabicore, the Support Vector Machines classifier is more accurate than other statistical classifiers. Our goal in this paper is to pave the way toward building advanced Moroccan dialect NLP tools such as morphological analyzer and machine translation system.

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A POS-Based Preordering Approach for English-to-Arabic Statistical Machine Translationiltering and rule application is used to ensure a fast and efficient reordering. The tests performed on the IWSLT2016 English-to-Arabic evaluation benchmark show a noticeable increase in the overall Blue Score for our system over the baseline PSMT system.