Name
Abstract | ||
|---|---|---|
Items in real-world recommender systems exhibit certain hierarchical structures. Similarly, user preferences also present hierarchical structures. Recent studies show that incorporating the hierarchy of items or user preferences can improve the performance of recommender systems. However, hierarchical structures are often not explicitly available, especially those of user preferences. Thus, there'... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TKDE.2018.2789443 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | Field | DocType |
Music,Recommender systems,Art,Films,Motion pictures,Clocks,Ice | Recommender system,Computer science,Artificial intelligence,Hierarchy,Machine learning | Journal |
Volume | Issue | ISSN |
30 | 6 | 1041-4347 |
Citations | PageRank | References |
6 | 0.44 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Suhang Wang | 1 | 859 | 51.38 |
| Jiliang Tang | 2 | 3323 | 140.81 |
| Yilin Wang | 3 | 163 | 9.77 |
| Huan Liu | 4 | 12695 | 741.34 |