Name
Abstract | ||
|---|---|---|
•We construct a Heterogeneous Bibliographic Network, which exploits semantics among the network objects.•We propose a GAN-based network embedding model to address the network sparsity problem.•We propose a citation recommendation model to produce personalized results corresponding to researchers' preferences.•We conduct extensive experiments on two real-world datasets and prove the significance of the proposed model. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.114888 | Expert Systems with Applications |
Keywords | DocType | Volume |
Recommender systems,Citation recommendation,Network embedding,Generative adversarial network,Deep learning,Sparsity | Journal | 180 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zafar Ali | 1 | 24 | 10.76 |
| Guilin Qi | 2 | 961 | 88.58 |
| Khan Muhammad | 3 | 986 | 67.67 |
| P Kefalas | 4 | 0 | 0.34 |
| Shah Khusro | 5 | 41 | 11.92 |