A Comprehensive Survey of Link Prediction Techniques for Social Network

Samad, Abdul and Qadir, Mamoona and Nawaz, Ishrat and Islam, Muhammad Arshad and Aleem, Muhammad (2020) A Comprehensive Survey of Link Prediction Techniques for Social Network. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 7 (23): 3. ISSN 2410-0218

[img]
Preview
Text (PDF)
eai.13-7-2018.163988.pdf - Published Version
Available under License Creative Commons Attribution No Derivatives.

Download (4MB) | Preview

Abstract

A growing trend of using social networking sites is attracting researchers to study and analyze different aspects of social network. Besides many problems, link prediction is a fascinating problem in the field of social network analysis (SNA). Link prediction, in social network analysis, is a task of identifying the missing links and predicting the new links. Several researchers have proposed solutions for the link prediction problem during the past two decades. However, there is a need to provide comprehensive overview of the significant contributions for a thorough analysis. The objective of this review is to summaries and discuss the existing link prediction algorithms in a common context for an unbiased analysis. The extensive review is presented by constructing the systematical category for proposed algorithms, selected problems, evaluation measures along with selected network datasets. Finally, applications of link prediction are discussed.

Item Type: Article
Uncontrolled Keywords: Link Prediction, Social Network, Survey
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor I.
Date Deposited: 11 Sep 2020 07:37
Last Modified: 11 Sep 2020 07:37
URI: https://eprints.eudl.eu/id/eprint/222

Actions (login required)

View Item View Item