Unsupervised Negative Link Prediction in Signed Social Networks
Joint Authors
Wang, Ying
Shen, Pengfei
Liu, Shufen
Han, Lu
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-30
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
It has been proved in a number of applications that it is useful to predict unknown social links, and link prediction has played an important role in sociological study.
Although there has been a surge of pertinent approaches to link prediction, most of them focus on positive link prediction while giving few attentions to the problem of inferring unknown negative links.
The inherent characteristics of negative relations present great challenges to traditional link prediction: ( 1 ) there are very few negative interaction data; ( 2 ) negative links are much sparser than positive links; ( 3 ) social data is often noisy, incomplete, and fast-evolved.
This paper intends to address this novel problem by solely leveraging structural information and further proposes the UN-PNMF framework based on the projective nonnegative matrix factorization, so as to incorporate network embedding and user’s property embedding into negative link prediction.
Empirical experiments on real-world datasets corroborate their effectiveness.
American Psychological Association (APA)
Shen, Pengfei& Liu, Shufen& Wang, Ying& Han, Lu. 2019. Unsupervised Negative Link Prediction in Signed Social Networks. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1196952
Modern Language Association (MLA)
Shen, Pengfei…[et al.]. Unsupervised Negative Link Prediction in Signed Social Networks. Mathematical Problems in Engineering No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1196952
American Medical Association (AMA)
Shen, Pengfei& Liu, Shufen& Wang, Ying& Han, Lu. Unsupervised Negative Link Prediction in Signed Social Networks. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1196952
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196952