000 02581cam a2200349 a 4500
003 EG-GiCUC
005 20250223031106.0
008 141113s2014 ua d f m 000 0 eng d
040 _aEG-GiCUC
_beng
_cEG-GiCUC
041 0 _aeng
049 _aDeposite
097 _aM.Sc
099 _aCai01.18.02.M.Sc.2014.Ah.I
100 0 _aAhmed Ibrahim Moussa Hussein Ali
245 1 0 _aImproving the automatic summarization of Arabic text depending on rhetorical structure theory /
_cAhmed Ibrahim Moussa Hussein Ali ; Supervised Mervat Gheith , Laila Nassef , Tarek Elghazaly
246 1 5 _aتحسين التلخيص الآلي للنصوص العربية اعتمادًا على نظرية التركيب البياني
260 _aCairo :
_bAhmed Ibrahim Moussa Hussein Ali ,
_c2014
300 _a114 Leaves :
_bcharts ;
_c25cm
502 _aThesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Sciences
520 _aNowadays, numerous documents, reports and articles are available in a digital form. Consequently, search engines retrieve an abundance of information. Besides, an overwhelming number of emails and documents floods users and agencies. Therefore, such retrieved documents need to be summarized. In this information explosion, the automatic text summarization proves to be an essential tool. Nevertheless, the key problem with the automatic text summarization process is that the target-summarized text is incoherent and deviates from the context of the original text. This problem emerges when statistical techniques are used for summarization. This thesis uses a semantic technique by adopting a Rhetorical Structure Theory. RST is a descriptive theory for a major aspect of the organization of natural texts. It extracts the semantics behind the text by identifying the most significant parts thereof. Here comes the role of this thesis as it introduces an infrastructure for applying RST to Arabic by collecting the Arabic rhetorical relations from different resources to build the rhetorical structure theory. However, the quality of RST summarization suffers when dealing with large documents
530 _aIssued also as CD
653 4 _aArabic text
653 4 _aRhetorical structure theory
653 4 _aRST
700 0 _aLaila Nassef ,
_eSupervisor
700 0 _aMervat Gheith ,
_eSupervisor
700 0 _aTarek Elghazaly ,
_eSupervisor
856 _uhttp://172.23.153.220/th.pdf
905 _aAml
_eCataloger
905 _aNazla
_eRevisor
942 _2ddc
_cTH
999 _c48203
_d48203