Link Prediction Methods in Bipartite Networks

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Özet

Nowadays, social networks, whose application areas are increasing day by day; Such as data mining, protein-gene interaction networks, online social networks, transport networks, academic information networks, and telecommunications networks. Many real-world complex networks have a naturel bipartite structure. In bipartite networks, which have become the focus of many researchers who have been dealing with social network analysis in recent years, connection estimation methods are the basic methods used to understand the structure of these networks. This study is a survey work that describes the connection in a bipartite network that is suitable for the nature of today's huge data networks. In this study, a bipartite network interface is an introductory guide for researchers who plan to work on this subject by examining the internal links and bipartite network projection methods.

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AlanDeğerDil
dc.contributor.authorAslan, Serpil
dc.contributor.authorKaya, Mehmet
dc.contributor.editorAdali, E
dc.date.accessioned2026-10-28T14:58:45.739512833Z
dc.date.available2026-10-28T14:58:45.739512833Z
dc.date.issued2017
dc.description.abstractNowadays, social networks, whose application areas are increasing day by day; Such as data mining, protein-gene interaction networks, online social networks, transport networks, academic information networks, and telecommunications networks. Many real-world complex networks have a naturel bipartite structure. In bipartite networks, which have become the focus of many researchers who have been dealing with social network analysis in recent years, connection estimation methods are the basic methods used to understand the structure of these networks. This study is a survey work that describes the connection in a bipartite network that is suitable for the nature of today's huge data networks. In this study, a bipartite network interface is an introductory guide for researchers who plan to work on this subject by examining the internal links and bipartite network projection methods.
dc.identifier.endpage1099
dc.identifier.isbn978-1-5386-0930-9
dc.identifier.startpage1095
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/3980
dc.identifier.wosWOS:000426856900207
dc.language.isotr
dc.publisherIEEE
dc.relation.conference2017 International Conference on Computer Science and Engineering (UBMK)
dc.relation.ispartof2017 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK)
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectKeywords Social Networks
dc.subjectLink Prediction
dc.subjectBipartite Networks
dc.subjectBipartite Network Projection
dc.subjectInternal Links
dc.subject.classificationComputer Science, Software Engineering
dc.subject.classificationComputer Science, Theory & Methods
dc.subject.classificationComputer Science
dc.titleLink Prediction Methods in Bipartite Networks
dc.typeConference Object
rdl.citation.wos4
rdl.conference.dateOCT 05-08, 2017
rdl.conference.placeAntalya, TURKEY
rdl.oa.statusclosed
rdl.source.indexWOS
rdl.wos.indexConference Proceedings Citation Index - Science (CPCI-S)