Soft computing techniques in mining web data for e-commerce applications / Waleed Ahmed Abdelerahman ; Supervised Sanaa Elola Hanafi , Neamat Elgayar

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Waleed Ahmed Abderahman

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Material type: Text

TextLanguage: English Publication details: Cairo : Waleed Ahmed Abdelrahman , 2014Description: 77 Leaves : 30cmOther title:

تقنيات الحسابات المرنة في التنقيب في بيانات الويب لتطبيقات التجارة الاليكترونية [Added title page title]

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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information- Department of Information Technology Summary: E-commerce can be improved by mining customer navigation patterns and providing recommendations for web pages or products that customer may be interested in. This emerges the need for a process that recommends the customized Web presentations or predicts the tailored Web contents to Web users according to their specific tastes or preferences. This process is called web recommendation or personalization. In this work, we aim to address improving the performance of Web recommendation through developing and employing Web data mining methods

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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	Cai01.20.01.M.Sc.2014.Wa.S (Browse shelf(Opens below))		Not for loan	01010110063840000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.20.01.M.Sc.2014.Wa.S (Browse shelf(Opens below))	63840.CD	Not for loan	01020110063840000

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

E-commerce can be improved by mining customer navigation patterns and providing recommendations for web pages or products that customer may be interested in. This emerges the need for a process that recommends the customized Web presentations or predicts the tailored Web contents to Web users according to their specific tastes or preferences. This process is called web recommendation or personalization. In this work, we aim to address improving the performance of Web recommendation through developing and employing Web data mining methods

Issued also as CD

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