A utility-based link prediction method in social networks

Li, Yongli1; Luo, Peng2; Fan, Zhi-ping1; Chen, Kun3; Liu, Jiaguo4

2017-07-16

10.1016/j.ejor.2016.12.041

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH   影响因子和分区

0377-2217

1872-6860

Link prediction is a fundamental task in social networks, with the goal of estimating the likelihood of a link between each node pair. It can be applied in many situations, such as friend discovery on social media platforms or co-author recommendations in collaboration networks. Compared to the numerous traditional methods, this paper introduces utility analysis to the link prediction method by considering that individual preferences are the main reason behind the decision to form links, and meanwhile it also focuses on the meeting process that is a latent variable during the process of forming links. Accordingly, the link prediction problem is formulated as a machine learning process with latent variables; therefore, an Expectation Maximization (EM, for short) algorithm is adopted and further developed to cope with the estimation problem. The performance of the present method is tested both on synthetic networks and on real-world datasets from social media networks and collaboration networks. All of the computational results illustrate that the proposed method yields more satisfying link prediction results than the selected benchmarks, and in particular, logistic regression, as a special case of the proposed method, provides the lower boundary of the likelihood function. (C) 2016 Elsevier B.V. All rights reserved.

Networks Link prediction Utility analysis EM algorithm Latent variable

SCI ; EI ; SSCI

英语

其他

Social Science Fund of Liaoning Province[L15CGL014]

Business & Economics ; Operations Research & Management Science

Management ; Operations Research & Management Science

WOS:000396952700025

ELSEVIER SCIENCE BV

20170203232163

Equivalence classes ; Learning algorithms ; Learning systems ; Networks (circuits) ; Social networking (online)

Electric Networks:703.1 ; Computer Software, Data Handling and Applications:723

ENGINEERING

Web of Science

1.Northeastern Univ, Sch Business Adm, Shenyang 110169, Peoples R China
2.Harbin Inst Technol, Sch Management, Harbin 150001, Peoples R China
3.South Univ Sci & Technol China, Dept Financial Math & Financial Engn, Shenzhen 518055, Peoples R China
4.Dalian Maritime Univ, Transportat Management Coll, Dalian 116026, Peoples R China

Li, Yongli,Luo, Peng,Fan, Zhi-ping,et al. A utility-based link prediction method in social networks[J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH,2017,260(2):693-705.

Li, Yongli,Luo, Peng,Fan, Zhi-ping,Chen, Kun,&Liu, Jiaguo.(2017).A utility-based link prediction method in social networks.EUROPEAN JOURNAL OF OPERATIONAL RESEARCH,260(2),693-705.

Li, Yongli,et al."A utility-based link prediction method in social networks".EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 260.2(2017):693-705.