Apriori algorithm for Arabic data using MapReduce
Other Title(s)
خوارزمية Apriori و استخدامها للنص العربي باستخدام نموذج MapReduce
Dissertant
al-Khudari, Ula Abd al-Nasir Hasan
Thesis advisor
Comitee Members
al-Halis, Ala Mustafa
al-Sayigh, Sana Wafa
University
Islamic University
Faculty
Faculty of Information Technology
Department
Information Technology
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2015
English Abstract
Aprioi is the most popular algorithm that is used to extract frequent itemsets from large data sets where these frequent itemsets can be used to generate association rules.
Such rules are used as a basis for discovering knowledge such as detecting unknown relationships and producing results which can be used for decision making and prediction.
When the data size is very large, both memory use and computational cost are very expensive.
And in this case single processor’s memory and CPU resources are very limited which make the algorithm performance inefficient.
Parallel and distributed computing is effective for improving algorithm performance.
In our research we propose a parallel Apriori approach for large volume of Arabic text document using MapReduce with enhanced speedup and performance, Apriori algorithm that has been popular to collect the itemsets frequently occurred in order to compose Association Rule, MapReduce is a scalable data processing tool that enables to process a massive volume of data in parallel.
The experiments show that the parallel Apriori approach can process large volume of Arabic text efficiently on a MapReduce with 16 computers, which can significantly improve the execution time and speedup and also generate strong association rules.
Main Subjects
Information Technology and Computer Science
No. of Pages
62
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Related work.
Chapter Three : Theoretical foundation.
Chapter Four : The proposed parallel apriori algorithm.
Chapter Five : Experimental results and evaluation.
Chapter Six : Conclusion and future work.
References.
American Psychological Association (APA)
al-Khudari, Ula Abd al-Nasir Hasan. (2015). Apriori algorithm for Arabic data using MapReduce. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-724514
Modern Language Association (MLA)
al-Khudari, Ula Abd al-Nasir Hasan. Apriori algorithm for Arabic data using MapReduce. (Master's theses Theses and Dissertations Master). Islamic University. (2015).
https://search.emarefa.net/detail/BIM-724514
American Medical Association (AMA)
al-Khudari, Ula Abd al-Nasir Hasan. (2015). Apriori algorithm for Arabic data using MapReduce. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-724514
Language
English
Data Type
Arab Theses
Record ID
BIM-724514