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19824

REDUCING ATTRIBUTES of FACEBOOK USERS USING ROUGH SET THEORY

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Last updated: 22 Jan 2023

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Abstract

Using social networks have become one of the daily activities that billions of peoples around the world do. So, great research efforts had been done to analyze and understand these virtual communities. Among other things, link prediction is a paramount task to analyze and understand these social networks. In this paper, we investigate link prediction problem using rough set theory to discard the irrelevant attributes that could be found in the profiles of Facebook users and the proposed work
induces accuracy 97.79%.

DOI

10.21608/ijicis.2016.19824

Keywords

Link Prediction, Social networks, Rough set theory, facebook, Self-Organization Map

Authors

First Name

W.

Last Name

Abdallah

MiddleName

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Affiliation

Dept. of Computer Science, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt.

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First Name

S.

Last Name

Sarhan

MiddleName

-

Affiliation

Dept. of Computer Science, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt.

Email

-

City

-

Orcid

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First Name

Samir

Last Name

Elmougy

MiddleName

-

Affiliation

Dept. of Computer Science, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt

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City

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Volume

16

Article Issue

4

Related Issue

1936

Issue Date

2016-10-01

Receive Date

2018-11-25

Publish Date

2016-10-01

Page Start

29

Page End

40

Print ISSN

1687-109X

Online ISSN

2535-1710

Article File

IJICIS_Volume 16_Issue 4_Pages 29-40.pdf

PDF . 2.6MB

Link

https://ijicis.journals.ekb.eg/article_19824.html

Detail API

https://ijicis.journals.ekb.eg/service?article_code=19824

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Original Article

Type Code

494

Publication Type

Journal

Publication Title

International Journal of Intelligent Computing and Information Sciences

Publication Link

https://ijicis.journals.ekb.eg/

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Article

Created At

22 Jan 2023