Enhanced Apriori algorithms’ : discovering patterns using the cloud or probabilistic range approach

مقدم أطروحة جامعية

Ali, Mir Dawar

مشرف أطروحة جامعية

Atum, Jalal Yusuf

أعضاء اللجنة

Awajan, Arafat
Ubayd, Nadim
al-Majali, Sufyan

الجامعة

جامعة الأميرة سمية للتكنولوجيا

الكلية

كلية الملك الحسين لعلوم الحوسبة

القسم الأكاديمي

قسم علم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2015

الملخص الإنجليزي

Finding frequent patterns using ‘Apriori’ algorithm has been an integral part of knowledge discovery science.

This algorithm is costly on large search spaces and therefore it is executed mainly on a limited portion of the search space to catch up with time and provide instant results.

This limitation effects the quality and the number of the derived patterns and therefore a need to modify the exisiting algorithm to come up with innovative algorithms’ firstly capable to be driven over multiple cores in the clouds to discover patterns over extensively large search space in a relatively faster time without compromising on the quality of the deliverables and secondly with a probabilistic range approach. Applying these core derivative algorithms’ on huge data resources already available for different business domains over the web, we should v be able to see patterns within this data and then make them useful based on the frequency measures inorder to later enhance and continuously learn to improve the decisions made based on these generated patterns .

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• الخوارزميات

عدد الصفحات

54

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-651035