Link Prediction in Complex Network via Penalizing Noncontribution Relations of Endpoints
Joint Authors
Tian, Hui
Zhu, Xuzhen
Tian, Yang
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-13
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Similarity based link prediction algorithms become the focus in complex network research.
Although endpoint degree as source of influence diffusion plays an important role in link prediction, some noncontribution links, also called noncontribution relations, involved in the endpoint degree serve nothing to the similarity between the two nonadjacent endpoints.
In this paper, we propose a novel link prediction algorithm to penalize those endpoints’ degrees including many null links in influence diffusion, namely, noncontribution relations penalization algorithm, briefly called NRP.
Seven mainstream baselines are introduced for comparison on nine benchmark datasets, and numerical analysis shows great improvement of accuracy performance, measured by the Area Under roc Curve (AUC).
At last, we simply discuss the complexity of our algorithm.
American Psychological Association (APA)
Zhu, Xuzhen& Tian, Yang& Tian, Hui. 2014. Link Prediction in Complex Network via Penalizing Noncontribution Relations of Endpoints. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1044272
Modern Language Association (MLA)
Zhu, Xuzhen…[et al.]. Link Prediction in Complex Network via Penalizing Noncontribution Relations of Endpoints. Mathematical Problems in Engineering No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1044272
American Medical Association (AMA)
Zhu, Xuzhen& Tian, Yang& Tian, Hui. Link Prediction in Complex Network via Penalizing Noncontribution Relations of Endpoints. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1044272
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1044272