Friend Recommendation Decision Systems via Multiple Social Network Alignment
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Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Today, almost all internet users have more than one social network account on different social networks for interaction with friends and other users. Gathering data from various networks to combined into a single node can be used for increasing the success rate of recommendation systems. In this study, data related to thousands of users in nine different social networks are used for successful recommendations to the users. The anchor method is used for topological alignment, and the relationship between nodes is taken into account for calculation. Also, the node similarity method is used to increase the success rate. In this method, the number of successful node matching is increased thanks to the feature selection criteria. An original node alignment and node similarity methods are proposed in the study. Because of combine both node alignment and node similarity method, the proposed method is very successful for the friend recommendation. © 2020 IEEE.
Açıklama
2020 International Conference on Decision Aid Sciences and Application, DASA 2020 -- 7 November 2020 through 9 November 2020 -- Virtual, Sakheer -- 166557
Anahtar Kelimeler
decision support, friend recommendation, node alignment, node similarity
Kaynak
2020 International Conference on Decision Aid Sciences and Application, DASA 2020
WoS Q Değeri
Scopus Q Değeri
N/A
