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003 | EG-GiCUC | ||
008 | 161103s2016 ua dh f m 000 0 eng d | ||
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_aEG-GiCUC _beng _cEG-GiCUC |
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041 | 0 | _aeng | |
049 | _aDeposite | ||
097 | _aM.Sc | ||
099 | _aCai01.18.02.M.Sc.2016.Sa.S | ||
100 | 0 | _aSamah Meghawry Mohamed Elsayed | |
245 | 1 | 0 |
_aSemantic extraction of Arabic multi-word expressions / _cSamah Meghawry Mohamed Elsayed ; Supervised Akram Ibrahim Salah , Abeer Elkorany , Tarek Elghazaly |
246 | 1 | 5 | _aالاستخراج الدالالي للمصطلحات متعددة الكلمات باللغة العربية |
260 |
_aCairo : _bSamah Meghawry Mohamed Elsayed , _c2016 |
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_a94 P. : _bcharts , facsimiles ; _c30cm |
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502 | _aThesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Science | ||
520 | _aMultiword expressions (MWEs) refer to any expression composed of two or more words repeated with each other more than one time along text with the same order. MWEs semantically have a meaning that can't be inferred from its candidates; this ambiguity caused a problem to many natural language processing (NLP) application such as tokenization, machine translation, information retrieval, text summarization, etc. as a consequence this ambiguity ends when such applications deal with MWEs as a one unit or word with spaces. Generally, there are three main approaches are used for extracting MEWs statistical approach, linguistic approach, alignment approach, or a combination of two or all of them. We have an assumption which assumes linguistic rules may enhance the obtained results from the statistical phase; so a hybrid approach used to extract Arabic MWEs from three different Arabic corpora; which combines the statistical approach that discover the repeated MWEs and its results enhanced using the linguistic approach. Our method extracted the bigram candidates from Arabic corpus, and it reported a 67% precision compared to previous work results which was 32%, and it evaluated by a human expert | ||
530 | _aIssued also as CD | ||
653 | 4 | _aMulti-Word Expirations (MWEs) | |
653 | 4 | _aNatural Language Processing (NLP) | |
653 | 4 | _aPart of Speech Tagging (POS) | |
700 | 0 |
_aAbeer Elkorany , _eSupervisor |
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700 | 0 |
_aAkram Ibrahim Salah , _eSupervisor |
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700 | 0 |
_aTarek Elghazaly , _eSupervisor |
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_aNazla _eRevisor |
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905 |
_aSamah _eCataloger |
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_2ddc _cTH |
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_c58427 _d58427 |