Name
Abstract | ||
|---|---|---|
•DBN- based classification model is proposed in this paper for web spam detection.•SMOTE and DAE algorithms is applied in DBN to improve the classification performance•The content and link feature is combined.•The results obtained in this paper is better than the existing systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.eswa.2017.12.016 | Expert Systems with Applications |
Keywords | Field | DocType |
Web spam,Web spam classification,SMOTE,Deep learning,DAE,DBN | User experience design,Search engine,Computer science,Deep belief network,Artificial intelligence,Deep learning,Machine learning,Spamdexing,The Internet | Journal |
Volume | Issue | ISSN |
96 | C | 0957-4174 |
Citations | PageRank | References |
2 | 0.38 | 29 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuancheng Li | 1 | 2 | 0.38 |
| Xiangqian Nie | 2 | 2 | 0.38 |
| Rong Huang | 3 | 38 | 6.09 |