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Optimizing memory utilization in main-memory cloud database / Ghada Mohamed Abdelmonem Afify ; Supervised Osman Hegazy , Ali Hamed Elbastawissy

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ghada Mohamed Abdelmonem Afify , 2016Description: 127 Leaves : charts , facsimiles ; 30cmOther title:
  • تحسين إستخدام الذاكرة الرئيسية فى قاعدة البيانات السحابية [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Computers and Information - Department of Information System Summary: A novel hybrid filtering approach (HFA) is introduced, which tracks both tuples and attributes access. A novel algorithm called HC_Apriori is introduced, which adapts the optimized Trie Apriori algorithm, employing a new optimization measure. The objective is to enhance the performance in terms of two metrics: Storage space and execution time. Real-world popular data mining datasets were used: Mushroom, chess, connect and accidents. Finally, the efficiency of the proposed HC_Apriori algorithm in optimizing memory utilization is proved in azure cloud environment
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.04.Ph.D.2016.Gh.O (Browse shelf(Opens below)) Not for loan 01010110073073000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.04.Ph.D.2016.Gh.O (Browse shelf(Opens below)) 73073.CD Not for loan 01020110073073000

Thesis (Ph.D.) - Cairo University - Faculty of Computers and Information - Department of Information System

A novel hybrid filtering approach (HFA) is introduced, which tracks both tuples and attributes access. A novel algorithm called HC_Apriori is introduced, which adapts the optimized Trie Apriori algorithm, employing a new optimization measure. The objective is to enhance the performance in terms of two metrics: Storage space and execution time. Real-world popular data mining datasets were used: Mushroom, chess, connect and accidents. Finally, the efficiency of the proposed HC_Apriori algorithm in optimizing memory utilization is proved in azure cloud environment

Issued also as CD

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