Name
Title | ||
|---|---|---|
Classification by multi-semantic meta path and active weight learning in heterogeneous information networks. |
Abstract | ||
|---|---|---|
•The complex correlations in Heterogeneous Information Network are represented by meta path.•Multi-semantic Meta path and jump path strengthen the associations between the nodes.•The active weight learning method is proposed for multiple kinds of meta-path.•The classification task in HINs reaches higher accuracy even with the small labeled data size.•The performance of our approach achieves significant improvement than other methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2019.01.044 | Expert Systems with Applications |
Keywords | Field | DocType |
Classification,Meta-path,Heterogeneous information network,Active weight learning,Similarity matrix | Information networks,Active learning,Computer science,Correlation,Artificial intelligence,Feature matrix,Complex network,Labeled data,Random forest,Machine learning,Semantics | Journal |
Volume | ISSN | Citations |
123 | 0957-4174 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong-ping Du | 1 | 9 | 3.22 |
| Wenyang Guo | 2 | 1 | 1.36 |
| Jingxuan Liu | 3 | 1 | 0.68 |
| Changqing Yao | 4 | 22 | 6.71 |