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New trends for building arabic language resources / Mohamed Abdelrahman Zahran Mohamed ; Supervised Amir Atyia , Mohsen Rashwan

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohamed Abdelrahman Zahran Mohamed , 2015Description: 87 P. : plans ; 30cmOther title:
  • اتجاهات جديدة لبناء موارد اللغة العربية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering Summary: Language resources are important factor in any natural language processing application. However, the language resource support for Arabic is not mature because the existing Arabic language resources are either scattered, inconsistent or even incomplete. To solve this problem, first, we automatically bootstrap a rich Arabic language resource leveraging the existing resources. Next, we build the largest statistical Arabic language resource, and then introduce a new technique to map this statistical Arabic resource to the English counterpart outperforming standard techniques in this task. Finally, using the new statistical methods we present a novel hoto here technique to link conventional Arabic language resources to English using cross lingual lexical substitution outperforming the state of the art system in this problem
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2015.Mo.N (Browse shelf(Opens below)) Not for loan 01010110067347000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2015.Mo.N (Browse shelf(Opens below)) 67347.CD Not for loan 01020110067347000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering

Language resources are important factor in any natural language processing application. However, the language resource support for Arabic is not mature because the existing Arabic language resources are either scattered, inconsistent or even incomplete. To solve this problem, first, we automatically bootstrap a rich Arabic language resource leveraging the existing resources. Next, we build the largest statistical Arabic language resource, and then introduce a new technique to map this statistical Arabic resource to the English counterpart outperforming standard techniques in this task. Finally, using the new statistical methods we present a novel hoto here technique to link conventional Arabic language resources to English using cross lingual lexical substitution outperforming the state of the art system in this problem

Issued also as CD

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