کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10368477 | 874781 | 2015 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Experimenting a discriminative possibilistic classifier with reweighting model for Arabic morphological disambiguation
ترجمه فارسی عنوان
آزمایش یک طبقه بندی احتمالی اختیاری با استفاده از مدل تعادلی برای ابهام مورفولوژی عربی
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کلمات کلیدی
تجزیه و تحلیل مورفولوژیکی، ابهام مورفولوژیکی، طبقه بندی احتمالی قابل تشخیص، مدل وزن مجدد
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
In this paper, we experiment a discriminative possibilistic classifier with a reweighting model for morphological disambiguation of Arabic texts. The main idea is to provide a possibilistic classifier that acquires automatically disambiguation knowledge from vocalized corpora and tests on non-vocalized texts. Initially, we determine all the possible analyses of vocalized words using a morphological analyzer. The values of their morphological features are exploited to train the classifier. The testing phase consists in identifying the accurate class value (i.e., a morphological feature) using the features of the preceding and the following words. The appropriate class is the one having the greatest value of a possibilistic measure computed over the training set. To discriminate the effect of each feature, we add the weights of the training attributes to this measure. To assess this approach, we carry out experiments on a corpus of Arabic stories and on the Arabic Treebank. We present results concerning all the morphological features and we discern to which degree the discriminative approach improves disambiguation rates and extract the dependency relationships among the features. The results reveal the contribution of possibility theory for resolving ambiguities in real applications. We also compare the success rates in modern versus classical Arabic texts. Finally, we try to evaluate the impact of the lexical likelihood in morphological disambiguation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Speech & Language - Volume 33, Issue 1, September 2015, Pages 67-87
Journal: Computer Speech & Language - Volume 33, Issue 1, September 2015, Pages 67-87
نویسندگان
Ibrahim Bounhas, Raja Ayed, Bilel Elayeb, Fabrice Evrard, Narjès Bellamine Ben Saoud,