Name
Title | ||
|---|---|---|
Community Discovery On Multi-View Social Networks Via Joint Regularized Nonnegative Matrix Triple Factorization |
Abstract | ||
|---|---|---|
In multi-view social networks field, a flexible Nonnegative Matrix Factorization (NMF) based framework is proposed which integrates multi-view relation data and feature data for community discovery. Benefit with a relaxed pairwise regularization and a novel orthogonal regularization, it outperforms the-state-of-art algorithms on five real-world datasets in terms of accuracy and NMI. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1587/transinf.2017EDP7004 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
data mining, community discovery, social network, nonnegative matrix factorization | Monad (category theory),Social network,Nonnegative matrix,Pattern recognition,Computer science,Non-negative matrix factorization,Factorization,Artificial intelligence | Journal |
Volume | Issue | ISSN |
E100D | 6 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liangliang Zhang | 1 | 0 | 1.35 |
| Longqi Yang | 2 | 0 | 2.70 |
| Yong Gong | 3 | 3 | 1.46 |
| ZhiSong Pan | 4 | 73 | 20.41 |
| Yanyan Zhang | 5 | 149 | 23.51 |
| GuYu Hu | 6 | 34 | 15.21 |