Name
Abstract | ||
|---|---|---|
Over the years, model-based approaches have shown their effectiveness in computing recommendation lists in different domains and settings. By relying on the computation of latent factors, they can recommend items with a very high level of accuracy. Unfortunately, when moving to the latent space, even if the model embeds content-based information, we miss references to the actual semantics of the r... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TKDE.2020.3010215 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Semantics,Recommender systems,Computational modeling,Data models,Robustness,Motion pictures,Resource description framework | Journal | 34 |
Issue | ISSN | Citations |
5 | 1041-4347 | 2 |
PageRank | References | Authors |
0.36 | 26 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vito Walter Anelli | 1 | 91 | 18.45 |
| Tommaso Di Noia | 2 | 1857 | 152.07 |
| Eugenio Di Sciascio | 3 | 1733 | 147.71 |
| Azzurra Ragone | 4 | 511 | 40.86 |
| Joseph Trotta | 5 | 22 | 2.28 |