نقدم ثلاث طرق تم تطويرها للمهمة المشتركة بشأن السخرية والكشف عن المعنويات باللغة العربية.نقدم خط الأساس الذي يستخدم ميزات شخصية N-Gram.نقترح أيضا طريقتين أكثر تطورا: شبكة عصبية متكررة مع تمثيل مستوى الكلمة وتصنيف الفرقة تعتمد على ميزات Word ومستوى الأحرف.لقد اخترنا تقديم نتائج من مصنف الفرقة، لكن لم يكن ناجحا للغاية مقارنة بأفضل النظم: 22/37 بشأن اكتشاف السخرية و 15/22 على اكتشاف المعنويات.لقد بدا أخيرا أن خط الأساس لدينا قد تم تحسينه وتغلب على تلك النتائج.
We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results.
References used
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