000			02122cam a2200337 a 4500
003			EG-GiCUC
005			20250223032328.0
008			190715s2018 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.20.04.M.Sc.2018.Kh.I
100	0		_aKhaled Ahmed Mohamed Ahmed
245	1	0	_aIntelligent approaches for social network analysis / _cKhaled Ahmed Mohamed Ahmed ; Supervised Ehab Ezzat , Aboulella Hassanien
246	1	5	_aسبل ذكية لتحليل شبكات التواصل الاجتماعي
260			_aCairo : _bKhaled Ahmed Mohamed Ahmed , _c2018
300			_a62 Leaves : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Computer and Information - Department of Information Systems
520			_aNowadays social networks are considered the fastest and the most important communication method which help persons or users to interact, exchange and communicate together from di erent countries. Social networks connect peo- ple from di erent places through online websites such as Facebook. Social networks analysis methods help in getting valuable insights for social net- works such as election by clustering the social networks' users, in industrial domain such as online branding pages or online advertising. Social networks analysis has two main urgent research gaps, the rst is community detection which helps in clustering or dividing the complex network into a set of clusters or groups, while the second is nding an accurate social network prediction approach for predicting posts' e ciency and performance for Facebook such as number of likes, shares and the interactions with audience
530			_aIssued also as CD
653		4	_aCommunity detection (CD)
653		4	_aSocial networks (SN)
653		4	_aUniform Resource Locator (URL)
700	0		_aAboulella Hassanien , _eSupervisor
700	0		_aEhab Ezzat , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aShimaa _eCataloger
942			_2ddc _cTH
999			_c72860 _d72860