Name
Abstract | ||
|---|---|---|
We address a novel semi-supervised learning strategy for Web Spam issue. The proposed approach explores graph construction which is the key of representing data semantical relationship, and emphasizes on label propagation from multi views under consistency criterion. Furthermore, we infer labels for the rest of the unlabeled nodes in fusing spectral space. Experiments on the Webspam Challenging dataset validate the efficiency and effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-68125-0_112 | PAKDD |
Keywords | Field | DocType |
fusing spectral space,web spam issue,label propagation,link feature,multi view,data semantical relationship,consistency criterion,graph construction,webspam challenging,semi supervised learning,web spam | Graph,Data mining,Consistency criterion,Label propagation,Computer science,Spectral space,Artificial intelligence,Machine learning,Spamdexing | Conference |
Volume | ISSN | ISBN |
5012 LNAI | 0302-9743 | 3-540-68124-8 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Yu-Jiu | 1 | 89 | 19.30 |
| Shuang-Hong Yang | 2 | 733 | 32.50 |
| Hu Bao-Gang | 3 | 1386 | 83.23 |