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96259

A Survey on Frequent Item Sets Mining for Big Data.

Article

Last updated: 22 Jan 2023

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Tags

Electrical Engineering

Abstract

Big Data" connects large-volume, complex, and increasing data sets with multiple independent sources. Nowadays, Big Data are speedily expanding in all science and engineering domains due to the rapid evolution of data, data storage, and the networking collection capabilities. Due to its variability, volume, and velocity, "Big Data mining" enjoys the ability of extracting constructive information from huge streams of data or datasets. Data mining includes exploring and analyzing big quantities of data in order to locate different molds for big data. "Frequent item sets Mining" is one of the most important tasks for discovering useful and meaningful patterns from large collections of data. Mining of association rules from frequent patterns from big data mining is of interest for many industries, for it can provide guidance in decision making processes; such as cross marketing, market basket analysis, promotion assortment, ...etc. The techniques of discovering association rules from data have traditionally focused on identifying the relationship between items predicting some aspect of human behavior;  usually buying behavior. This paper provides a review on different techniques for mining frequent item sets.

DOI

10.21608/bfemu.2020.96259

Keywords

Association Rule Mining, Data mining, Frequent Item sets, Big Data, Frequent Pattern Mining, Apriori, FP-Growth

Authors

First Name

Engy

Last Name

El-Shafaiy

MiddleName

Abd El-maboud

Affiliation

Computers and Systems Department, Faculty of Engineering, Mansoura University, Egypt

Email

engy_eng@yahoo.com

City

-

Orcid

-

First Name

Ali

Last Name

El-Desouky

MiddleName

Ibrahim

Affiliation

Computers and Systems Department, Faculty of Engineering, Mansoura University, Egypt

Email

-

City

-

Orcid

-

First Name

Yousry

Last Name

AbdulAzeem

MiddleName

Mohamed

Affiliation

Computers and Systems Department, Faculty of Engineering, Mansoura University, Egypt

Email

yousry@mans.edu.eg

City

-

Orcid

-

Volume

40

Article Issue

5

Related Issue

14486

Issue Date

2015-12-01

Receive Date

2015-12-30

Publish Date

2020-12-01

Page Start

12

Page End

23

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 40_Issue 5_Pages 12-23.pdf

PDF . 620.3kB

Link

https://bfemu.journals.ekb.eg/article_96259.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=96259

Order

2

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023