A Comprehensive Survey of Link Prediction Techniques for Social Network
A growing trend of using social networking sites is attracting researchers to study and analyze differentaspects of social network. Besides many problems, link prediction is a fascinating problem in the field of socialnetwork analysis (SNA). Link prediction, in social network analysis, is a task of...
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European Alliance for Innovation (EAI)
2020-05-01
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Online Access: | https://eudl.eu/pdf/10.4108/eai.13-7-2018.163988 |
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doaj-e86e71c7acb24e27906180db31fd0dd42020-11-25T02:59:31ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Industrial Networks and Intelligent Systems2410-02182020-05-0172310.4108/eai.13-7-2018.163988A Comprehensive Survey of Link Prediction Techniques for Social NetworkAbdul Samad0Mamoona Qadir1Ishrat Nawaz2Muhammad Islam3Muhammad Aleem4Capital University of Science and Technology, Islamabad PakistanKhwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan PakistanThe Islamia University of Bahawalpur, Bahawalpur PakistanFAST-National University of Computer and Emerging Sciences, Islamabad PakistanFAST-National University of Computer and Emerging Sciences, Islamabad PakistanA growing trend of using social networking sites is attracting researchers to study and analyze differentaspects of social network. Besides many problems, link prediction is a fascinating problem in the field of socialnetwork analysis (SNA). Link prediction, in social network analysis, is a task of identifying the missing linksand predicting the new links. Several researchers have proposed solutions for the link prediction problemduring the past two decades. However, there is a need to provide comprehensive overview of the significantcontributions for a thorough analysis. The objective of this review is to summaries and discuss the existinglink prediction algorithms in a common context for an unbiased analysis. The extensive review is presentedby constructing the systematical category for proposed algorithms, selected problems, evaluation measuresalong with selected network datasets. Finally, applications of link prediction are discussed.https://eudl.eu/pdf/10.4108/eai.13-7-2018.163988link predictionsocial networksurvey |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Abdul Samad Mamoona Qadir Ishrat Nawaz Muhammad Islam Muhammad Aleem |
spellingShingle |
Abdul Samad Mamoona Qadir Ishrat Nawaz Muhammad Islam Muhammad Aleem A Comprehensive Survey of Link Prediction Techniques for Social Network EAI Endorsed Transactions on Industrial Networks and Intelligent Systems link prediction social network survey |
author_facet |
Abdul Samad Mamoona Qadir Ishrat Nawaz Muhammad Islam Muhammad Aleem |
author_sort |
Abdul Samad |
title |
A Comprehensive Survey of Link Prediction Techniques for Social Network |
title_short |
A Comprehensive Survey of Link Prediction Techniques for Social Network |
title_full |
A Comprehensive Survey of Link Prediction Techniques for Social Network |
title_fullStr |
A Comprehensive Survey of Link Prediction Techniques for Social Network |
title_full_unstemmed |
A Comprehensive Survey of Link Prediction Techniques for Social Network |
title_sort |
comprehensive survey of link prediction techniques for social network |
publisher |
European Alliance for Innovation (EAI) |
series |
EAI Endorsed Transactions on Industrial Networks and Intelligent Systems |
issn |
2410-0218 |
publishDate |
2020-05-01 |
description |
A growing trend of using social networking sites is attracting researchers to study and analyze differentaspects of social network. Besides many problems, link prediction is a fascinating problem in the field of socialnetwork analysis (SNA). Link prediction, in social network analysis, is a task of identifying the missing linksand predicting the new links. Several researchers have proposed solutions for the link prediction problemduring the past two decades. However, there is a need to provide comprehensive overview of the significantcontributions for a thorough analysis. The objective of this review is to summaries and discuss the existinglink prediction algorithms in a common context for an unbiased analysis. The extensive review is presentedby constructing the systematical category for proposed algorithms, selected problems, evaluation measuresalong with selected network datasets. Finally, applications of link prediction are discussed. |
topic |
link prediction social network survey |
url |
https://eudl.eu/pdf/10.4108/eai.13-7-2018.163988 |
work_keys_str_mv |
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