Name
Abstract | ||
|---|---|---|
•A hybrid approach to learn and represent users’ preference knowledge.•Users’ preference knowledge representation supplements ratings prediction.•Extending latent factor model to include acquired preference knowledge.•Experiments on Amazon products datasets shows performance improvements. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.eswa.2019.04.047 | Expert Systems with Applications |
Keywords | Field | DocType |
User preference prediction,Text summarization,Deep learning embedding | Probabilistic matrix factorization,Automatic summarization,Architecture,Information retrieval,Computer science,Recurrent neural network,Artificial intelligence,Deep learning,Topic analysis,Machine learning | Journal |
Volume | ISSN | Citations |
132 | 0957-4174 | 2 |
PageRank | References | Authors |
0.36 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| James Chambua | 1 | 10 | 1.78 |
| Zhendong Niu | 2 | 548 | 67.31 |
| Yifan Zhu | 3 | 30 | 7.34 |