Name
Abstract | ||
|---|---|---|
In this paper, a novel Deep Multi-view Joint Clustering (DMJC) framework is proposed, where multiple deep embedded features, multi-view fusion mechanism, and clustering assignments can be learned simultaneously. Through the joint learning strategy, the clustering-friendly multi-view features and useful multi-view complementary inform... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TKDE.2020.2973981 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Clustering methods,Feature extraction,Electronic mail,Correlation,Learning systems,Clustering algorithms,Machine learning | Journal | 33 |
Issue | ISSN | Citations |
11 | 1041-4347 | 3 |
PageRank | References | Authors |
0.38 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Xie | 1 | 407 | 27.48 |
| Bingqian Lin | 2 | 6 | 2.46 |
| Yanyun Qu | 3 | 216 | 38.66 |
| Cui-Hua Li | 4 | 74 | 13.24 |
| Wensheng Zhang | 5 | 323 | 28.76 |
| Lizhuang Ma | 6 | 498 | 100.70 |
| Yonggang Wen | 7 | 2512 | 156.47 |
| Dacheng Tao | 8 | 19032 | 747.78 |