Querying in stream data / Asmaa Fawzy Awad Allah Hassan ; Supervised Osman Hegazy , Hoda Mokhtar

By:

Asmaa Fawzy Awad Allah Hassan

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Material type: Text

TextLanguage: English Publication details: Cairo : Asmaa Fawzy Awad Allah Hassan , 2012Description: 82Leaves : charts , facsimiles ; 30cmOther title:

الاستعلام فى البيانات المتدفقة [Added title page title]

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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Systems Summary: Qutlier detection is a vital research problem in data mining community that aims to find out useful irregular and abnormal patterns hidden in large sensory datasets . Detecting outliers in Wireless Sensor Networks (WSNs ) is an important issue to sort out data , encounter noise and discover interesting events in the physical environment

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Item type	Current library	Home library	Call number	Copy number	Status	Barcode
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.20.04.M.Sc.2012.As.Q (Browse shelf(Opens below))		Not for loan	01010110058085000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.20.04.M.Sc.2012.As.Q (Browse shelf(Opens below))	58085.CD	Not for loan	01020110058085000

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Previous	Cai01.20.04.M.Sc.2011.Re.S Supporting user interface design using patterns /	Cai01.20.04.M.Sc.2012.Ak.A The application of cloud computing in e-government systems /	Cai01.20.04.M.Sc.2012.Ak.A The application of cloud computing in e-government systems /	Cai01.20.04.M.Sc.2012.As.Q Querying in stream data /	Cai01.20.04.M.Sc.2012.As.Q Querying in stream data /	Cai01.20.04.M.Sc.2012.Ay.E An effective model for automatic text summarization /	Cai01.20.04.M.Sc.2012.Ay.E An effective model for automatic text summarization /	Next

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Systems

Qutlier detection is a vital research problem in data mining community that aims to find out useful irregular and abnormal patterns hidden in large sensory datasets . Detecting outliers in Wireless Sensor Networks (WSNs ) is an important issue to sort out data , encounter noise and discover interesting events in the physical environment

Issued also as CD

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