Name
Abstract | ||
|---|---|---|
Analyzing the underlying social network is very important for the development of online applications. Owing to the increasingly growing size of these networks, parallel techniques play important roles in many network analysis tasks. In this paper, we explore the link sign prediction problem in large-scale online social networks, and propose a parallel approach, called PLSP, to solve the problem. S... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1093/comjnl/bxt062 | The Computer Journal |
Keywords | Field | DocType |
social network analysis,link sign prediction,parallel training,feature selection | Social network,Computer science,Theoretical computer science,Distributed computing | Journal |
Volume | Issue | ISSN |
57 | 7 | 0010-4620 |
Citations | PageRank | References |
1 | 0.35 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiufeng Zhou | 1 | 6 | 0.75 |
| Lixin Han | 2 | 45 | 4.50 |
| Yuan Yao | 3 | 234 | 28.34 |
| Xiaoqin Zeng | 4 | 1 | 0.35 |
| Feng Xu | 5 | 270 | 28.53 |