Table 3 Performance comparisons of different methods.
From: Explicit intent enhanced contrastive learning with denoising networks for sequential recommendation
Dataset | Toys | Sports | Beauty | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Metrics | HR | NDCG | HR | NDCG | HR | NDCG | ||||||
@5 | @20 | @5 | @20 | @5 | @20 | @5 | @20 | @5 | @20 | @5 | @20 | |
BPR | 0.0120 | 0.0312 | 0.0082 | 0.0136 | 0.0141 | 0.0323 | 0.0091 | 0.0142 | 0.0212 | 0.0589 | 0.0130 | 0.0236 |
GRU4Rec | 0.0097 | 0.0301 | 0.0059 | 0.0116 | 0.0162 | 0.0421 | 0.0103 | 0.0186 | 0.0111 | 0.0478 | 0.0058 | 0.0104 |
Caser | 0.0166 | 0.0420 | 0.0107 | 0.0179 | 0.0154 | 0.0399 | 0.0114 | 0.0178 | 0.0251 | 0.0643 | 0.0145 | 0.0298 |
SASRec | 0.0463 | 0.0941 | 0.0306 | 0.0441 | 0.0206 | 0.0497 | 0.0135 | 0.0216 | 0.0374 | 0.0901 | 0.0241 | 0.0387 |
BERT4Rec | 0.0274 | 0.0688 | 0.0174 | 0.0291 | 0.0217 | 0.0604 | 0.0143 | 0.0251 | 0.0410 | 0.0914 | 0.0261 | 0.0403 |
\(S^3\text {-Rec}_\text {ISP}\) | 0.0143 | 0.0235 | 0.0123 | 0.0162 | 0.0121 | 0.0344 | 0.0084 | 0.0146 | 0.0189 | 0.0487 | 0.0115 | 0.0198 |
DSSRec | 0.0447 | 0.0942 | 0.0297 | 0.0437 | 0.0209 | 0.0499 | 0.0139 | 0.0221 | 0.0408 | 0.0894 | 0.0263 | 0.0399 |
CL4SRec | 0.0503 | 0.0990 | 0.0392 | 0.0506 | 0.0231 | 0.0557 | 0.0146 | 0.0238 | 0.0401 | 0.0974 | 0.0268 | 0.0428 |
CoSeRec | 0.0533 | 0.1037 | 0.0370 | 0.0513 | 0.0290 | 0.0636 | 0.0196 | 0.0293 | 0.0504 | 0.1034 | 0.0339 | 0.0487 |
ICLRec | 0.0598 | 0.1138 | 0.0404 | 0.0557 | 0.0283 | 0.0641 | 0.0182 | 0.0285 | 0.0500 | 0.1058 | 0.0326 | 0.0483 |
IOCRec | 0.0545 | 0.1133 | 0.0297 | 0.0465 | 0.0293 | 0.0684 | 0.0166 | 0.0279 | 0.0511 | 0.1126 | 0.0312 | 0.0490 |
EICD-Rec | 0.0663 | 0.1184 | 0.0469 | 0.0614 | 0.0305 | 0.0667 | 0.0203 | 0.0306 | 0.0580 | 0.1130 | 0.0397 | 0.0553 |
Improv. | 10.87% | 4.04% | 16.09% | 10.23% | 4.10% | − 2.49% | 3.57% | 4.44% | 13.50% | 0.36% | 17.11% | 12.86% |