Research Article
Dynamic and Static Features-Aware Recommendation with Graph Neural Networks
Table 2
Performance comparison of different methods.
| | Datasets | | Metrics | ML_100k | ML_1M | | Recall@N | NDCG@N | Recall@N | NDCG@N |
| | ICF | 0.1642 | 0.2913 | 0.1504 | 0.2030 | | PMF | 0.2303 | 0.3061 | 0.1943 | 0.2301 | | DMF | 0.3396 | 0.3562 | 0.2215 | 0.2472 | | Wide&Deep | 0.3402 | 0.3797 | 0.2502 | 0.2613 | | NGCF | 0.3487 | 0.4225 | 0.2637 | 0.2947 | | DGCF | 0.3339 | 0.4057 | 0.2973 | 0.3264 | | Ours | 0.3672 | 0.4470 | 0.3054 | 0.3421 |
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