Hyperparameters for MGS

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rate	[0.01 to 0.0001]
Batch Size	[16, 20, 32, 64, 80, 128]
L2 Penality	[0.00001, 0.0001, 0.000001, 0.001]
Dropout	[0.1,0.2,0.3, 0.5]
Epoch	[10, 12, 15, 20, 25]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.288
• Standard deviation: 0.053
• Maximum value: 0.381
• Minimum value: 0.204

Parameters/Metrics	MRR@20
MGS-epoch=12-lr=0.0045-batch_size=64-l2=0.0001-dropout=0.5	0.325
MGS-epoch=12-lr=0.0034-batch_size=64-l2=0.001-dropout=0.3;	0.250
MGS-epoch=12-lr=0.01-batch_size=64-l2=0.0001-dropout=0.5;	0.313
MGS-epoch=12-lr=0.0067-batch_size=64-l2=0.0001-dropout=0.1;	0.315
MGS-epoch=12-lr=0.0045-batch_size=128-l2=0.001-dropout=0.1	0.257
MGS-epoch=12-lr=0.01-batch_size=32-l2=0.0001-dropout=0.1	0.289
MGS-epoch=12-lr=0.0078-batch_size=128-l2=1e-05-dropout=0.2	0.353
MGS-epoch=12-lr=0.0045-batch_size=128-l2=0.0001-dropout=0.3	0.352
MGS-epoch=12-lr=0.0034-batch_size=32-l2=1e-06-dropout=0.2	0.351
MGS-epoch=12-lr=0.0056-batch_size=128-l2=0.001-dropout=0.2	0.264
MGS-epoch=12-lr=0.0023-batch_size=64-l2=0.001-dropout=0.5	0.261
MGS-epoch=12-lr=0.0045-batch_size=32-l2=0.001-dropout=0.5	0.216
MGS-epoch=12-lr=0.0067-batch_size=32-l2=0.001-dropout=0.5	0.212
MGS-epoch=12-lr=0.0089-batch_size=32-l2=0.0001-dropout=0.1	0.275
MGS-epoch=12-lr=0.0078-batch_size=32-l2=0.001-dropout=0.5	0.214
MGS-epoch=20-lr=0.01-batch_size=16-l2=0.001-dropout=0.5	0.204
MGS-epoch=10-lr=0.0023-batch_size=32-l2=0.0001-dropout=0.5	0.317
MGS-epoch=20-lr=0.0056-batch_size=64-l2=1e-05-dropout=0.1	0.356
MGS-epoch=15-lr=0.0034-batch_size=32-l2=0.001-dropout=0.3	0.241
MGS-epoch=20-lr=1e-04-batch_size=128-l2=1e-05-dropout=0.5	0.351
MGS-epoch=20-lr=0.0034-batch_size=16-l2=0.0001-dropout=0.5	0.276
MGS-epoch=20-lr=0.0034-batch_size=32-l2=0.001-dropout=0.3	0.230
MGS-epoch=20-lr=0.0056-batch_size=16-l2=1e-06-dropout=0.2	0.312
MGS-epoch=10-lr=0.0045-batch_size=128-l2=1e-05-dropout=0.2	0.381
MGS-epoch=15-lr=0.0067-batch_size=16-l2=1e-05-dropout=0.5	0.286

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.272
• Standard deviation: 0.018
• Maximum value: 0.293
• Minimum value: 0.217

Parameters/Metrics	MRR@20
MGS-epoch=25-lr=0.0034-batch_size=64-l2=0.0001-dropout=0.2	0.291
MGS-epoch=15-lr=0.0045-batch_size=32-l2=0.001-dropout=0.2	0.268
MGS-epoch=20-lr=0.0067-batch_size=80-l2=1e-05-dropout=0.6	0.290
MGS-epoch=20-lr=0.0078-batch_size=128-l2=0.001-dropout=0.1	0.265
MGS-epoch=25-lr=0.0023-batch_size=128-l2=0.001-dropout=0.6	0.272
MGS-epoch=10-lr=0.0056-batch_size=128-l2=0.001-dropout=0.3	0.271
MGS-epoch=20-lr=0.0023-batch_size=20-l2=0.0001-dropout=0.2	0.289
MGS-epoch=25-lr=0.0012-batch_size=32-l2=0.0001-dropout=0.1	0.284
MGS-epoch=15-lr=0.0067-batch_size=128-l2=1e-05-dropout=0.3	0.290
MGS-epoch=25-lr=0.0023-batch_size=32-l2=0.001-dropout=0.6	0.274
MGS-epoch=25-lr=0.01-batch_size=128-l2=1e-05-dropout=0.1	0.273
MGS-epoch=20-lr=0.0034-batch_size=64-l2=0.001-dropout=0.6	0.275
MGS-epoch=10-lr=0.0067-batch_size=32-l2=1e-05-dropout=0.1	0.278
MGS-epoch=25-lr=0.0023-batch_size=20-l2=1e-05-dropout=0.3	0.288
MGS-epoch=25-lr=0.0012-batch_size=128-l2=0.001-dropout=0.2	0.258
MGS-epoch=25-lr=0.0034-batch_size=20-l2=1e-05-dropout=0.6	0.282
MGS-epoch=25-lr=0.0089-batch_size=20-l2=0.001-dropout=0.3	0.224
MGS-epoch=10-lr=0.0045-batch_size=80-l2=0.0001-dropout=0.7	0.293
MGS-epoch=10-lr=0.0045-batch_size=32-l2=0.001-dropout=0.5	0.278
MGS-epoch=15-lr=0.0078-batch_size=16-l2=1e-06-dropout=0.3	0.272
MGS-epoch=10-lr=0.0034-batch_size=16-l2=0.001-dropout=0.3	0.260
MGS-epoch=15-lr=0.0078-batch_size=16-l2=0.001-dropout=0.1	0.217
MGS-epoch=15-lr=0.0067-batch_size=32-l2=1e-05-dropout=0.1	0.269
MGS-epoch=20-lr=0.0067-batch_size=128-l2=0.001-dropout=0.2	0.274

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.396
• Standard deviation: 0.106
• Maximum value: 0.568
• Minimum value: 0.173

Parameters/Metrics	MRR@20
MGS-epoch=12-lr=0.0056-batch_size=32-l2=1e-05-dropout=0.2	0.478
MGS-epoch=12-lr=0.0023-batch_size=128-l2=0.001-dropout=0.2	0.391
MGS-epoch=12-lr=0.0078-batch_size=32-l2=0.0001-dropout=0.5	0.390
MGS-epoch=12-lr=0.0034-batch_size=64-l2=1e-05-dropout=0.5	0.526
MGS-epoch=12-lr=0.0078-batch_size=32-l2=0.001-dropout=0.1	0.269
MGS-epoch=12-lr=1e-04-batch_size=32-l2=0.001-dropout=0.5	0.256
MGS-epoch=12-lr=0.0056-batch_size=128-l2=0.001-dropout=0.1	0.348
MGS-epoch=12-lr=0.0023-batch_size=128-l2=0.0001-dropout=0.3	0.492
MGS-epoch=12-lr=0.0045-batch_size=32-l2=1e-05-dropout=0.5	0.488
MGS-epoch=12-lr=0.0012-batch_size=64-l2=0.001-dropout=0.3	0.369
MGS-epoch=20-lr=0.0045-batch_size=32-l2=0.0001-dropout=0.5	0.404
MGS-epoch=15-lr=1e-04-batch_size=32-l2=1e-06-dropout=0.3	0.448
MGS-epoch=10-lr=0.0067-batch_size=16-l2=0.001-dropout=0.5	0.205
MGS-epoch=10-lr=0.0067-batch_size=64-l2=0.001-dropout=0.3	0.291
MGS-epoch=15-lr=0.0012-batch_size=16-l2=0.001-dropout=0.3	0.173
MGS-epoch=20-lr=0.0023-batch_size=16-l2=1e-05-dropout=0.5	0.376
MGS-epoch=20-lr=0.0012-batch_size=128-l2=0.001-dropout=0.2	0.428
MGS-epoch=10-lr=1e-04-batch_size=16-l2=1e-06-dropout=0.2	0.381
MGS-epoch=15-lr=0.0056-batch_size=32-l2=0.0001-dropout=0.1	0.401
MGS-epoch=15-lr=0.0089-batch_size=16-l2=0.0001-dropout=0.5	0.269
MGS-epoch=15-lr=0.0067-batch_size=32-l2=0.0001-dropout=0.5	0.396
MGS-epoch=20-lr=0.0078-batch_size=16-l2=0.0001-dropout=0.5	0.317
MGS-epoch=20-lr=0.0078-batch_size=128-l2=1e-05-dropout=0.3	0.568
MGS-epoch=15-lr=1e-04-batch_size=32-l2=0.001-dropout=0.1	0.259
MGS-epoch=10-lr=0.0034-batch_size=128-l2=0.001-dropout=0.3	0.361
MGS-epoch=15-lr=0.0067-batch_size=16-l2=1e-06-dropout=0.5	0.378
MGS-epoch=20-lr=0.0012-batch_size=32-l2=0.001-dropout=0.5	0.305
MGS-epoch=10-lr=0.0078-batch_size=16-l2=1e-05-dropout=0.2	0.364
MGS-epoch=20-lr=0.0078-batch_size=16-l2=0.0001-dropout=0.2	0.325
MGS-epoch=20-lr=0.0023-batch_size=64-l2=1e-05-dropout=0.2	0.518
MGS-epoch=20-lr=1e-04-batch_size=32-l2=0.001-dropout=0.1	0.272
MGS-epoch=10-lr=0.0067-batch_size=64-l2=0.001-dropout=0.3	0.299
MGS-epoch=20-lr=0.0078-batch_size=32-l2=1e-05-dropout=0.3	0.492
MGS-epoch=15-lr=0.0056-batch_size=128-l2=1e-06-dropout=0.5	0.562
MGS-epoch=10-lr=0.0034-batch_size=32-l2=1e-05-dropout=0.5	0.468
MGS-epoch=15-lr=0.0023-batch_size=128-l2=1e-06-dropout=0.5	0.544
MGS-epoch=10-lr=0.0089-batch_size=128-l2=0.001-dropout=0.3	0.319
MGS-epoch=15-lr=0.0012-batch_size=64-l2=1e-06-dropout=0.5	0.544
MGS-epoch=15-lr=0.0056-batch_size=32-l2=1e-06-dropout=0.3	0.512
MGS-epoch=10-lr=0.0056-batch_size=128-l2=0.0001-dropout=0.3	0.479
MGS-epoch=20-lr=0.0023-batch_size=64-l2=1e-06-dropout=0.3	0.557

Hyperparameters for GNRRW

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rate	[0.01 to 0.0001]
Batch Size	[20, 32, 64, 100, 128, 200, 256]
Embedding Size	[16, 32, 64, 80, 100, 128, 200]
L2 Penality	[0.01,0.0003, 0.000001, 0.0005, 0.0001]
Epochs	[10, 15, 20, 25, 30]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.383
• Standard deviation: 0.010
• Maximum value: 0.397
• Minimum value: 0.337

Parameters/Matrics	MRR@20
GNRRW-epoch=10-lr=0.0089-batch_size=200-l2=1e-05	0.3906
GNRRW-epoch=15-lr=0.0089-batch_size=200-l2=1e-05	0.3906
GNRRW-epoch=10-lr=0.0056-batch_size=200-l2=1e-05	0.3866
GNRRW-epoch=10-lr=0.0089-batch_size=32-l2=1e-05	0.3849
GNRRW-epoch=15-lr=0.0012-batch_size=20-l2=1e-05	0.3784
GNRRW-epoch=20-lr=0.0023-batch_size=200-l2=1e-05	0.3930
GNRRW-epoch=10-lr=0.0089-batch_size=20-l2=1e-05	0.3515
GNRRW-epoch=20-lr=0.01-batch_size=20-l2=1e-05	0.3367
GNRRW-epoch=10-lr=0.01-batch_size=32-l2=1e-05	0.3707
GNRRW-epoch=15-lr=1e-04-batch_size=20-l2=1e-05	0.3858
GNRRW-epoch=10-lr=0.0023-batch_size=20-l2=1e-05	0.3760
GNRRW-epoch=15-lr=0.0023-batch_size=128-l2=1e-05	0.3885
GNRRW-epoch=20-lr=0.01-batch_size=100-l2=1e-05	0.3859
GNRRW-epoch=20-lr=0.0034-batch_size=100-l2=1e-05	0.3912
GNRRW-epoch=15-lr=0.0056-batch_size=20-l2=1e-05	0.3743
GNRRW-epoch=20-lr=0.0023-batch_size=100-l2=1e-05	0.3872
GNRRW-epoch=20-lr=0.0089-batch_size=100-l2=1e-05	0.3926
GNRRW-epoch=15-lr=0.0045-batch_size=128-l2=1e-05	0.3834
GNRRW-epoch=10-lr=0.0023-batch_size=100-l2=1e-05	0.3936
GNRRW-epoch=10-lr=0.0045-batch_size=20-l2=1e-05	0.3732
GNRRW-epoch=10-lr=1e-04-batch_size=100-l2=1e-05	0.3834
GNRRW-epoch=10-lr=0.0056-batch_size=128-l2=1e-05	0.3863
GNRRW-epoch=15-lr=0.0034-batch_size=32-l2=1e-05	0.3847
GNRRW-epoch=20-lr=0.0056-batch_size=100-l2=1e-05	0.3817
GNRRW-epoch=10-lr=0.0034-batch_size=32-l2=1e-05	0.3849
GNRRW-epoch=20-lr=0.0089-batch_size=32-l2=1e-05	0.3780
GNRRW-epoch=15-lr=0.01-batch_size=128-l2=1e-05	0.3941
GNRRW-epoch=20-lr=1e-04-batch_size=100-l2=1e-05	0.3812
GNRRW-epoch=15-lr=0.0089-batch_size=128-l2=1e-05	0.3913
GNRRW-epoch=15-lr=0.0089-batch_size=100-l2=1e-05	0.3868
GNRRW-epoch=15-lr=0.0067-batch_size=100-l2=1e-05	0.3904
GNRRW-epoch=10-lr=0.0045-batch_size=32-l2=1e-05	0.3785
GNRRW-epoch=10-lr=0.0078-batch_size=20-l2=1e-05	0.3648
GNRRW-epoch=20-lr=0.0045-batch_size=200-l2=1e-05	0.3832
GNRRW-epoch=10-lr=0.0034-batch_size=128-l2=1e-05	0.3929
GNRRW-epoch=15-lr=0.0012-batch_size=32-l2=1e-05	0.3873
GNRRW-epoch=20-lr=0.0056-batch_size=32-l2=1e-05	0.3856
GNRRW-epoch=20-lr=0.0067-batch_size=20-l2=1e-05	0.3699
GNRRW-epoch=10-lr=0.0023-batch_size=128-l2=1e-05	0.3971
GNRRW-epoch=10-lr=0.0078-batch_size=32-l2=1e-05	0.3840
GNRRW-epoch=15-lr=0.0056-batch_size=100-l2=1e-05	0.3830
GNRRW-epoch=15-lr=1e-04-batch_size=100-l2=1e-05	0.3771
GNRRW-epoch=15-lr=0.0089-batch_size=128-l2=1e-05	0.3891
GNRRW-epoch=10-lr=0.0056-batch_size=128-l2=1e-05	0.3879
GNRRW-epoch=15-lr=0.0023-batch_size=20-l2=1e-05	0.3747
GNRRW-epoch=10-lr=0.01-batch_size=100-l2=1e-05	0.3937
GNRRW-epoch=15-lr=0.0034-batch_size=200-l2=1e-05	0.3922
GNRRW-epoch=15-lr=0.0034-batch_size=128-l2=1e-05	0.3884
GNRRW-epoch=20-lr=0.0067-batch_size=100-l2=1e-05	0.3857

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.215
• Standard deviation: 0.037
• Maximum value: 0.257
• Minimum value: 0.059

Parameters/Matrics	MRR@20
GNRRW-epoch=25-lr=0.00667-batch_size=256-embedding_size=128-l2=1e-05	0.190
GNRRW-epoch=15-lr=0.00778-batch_size=128-embedding_size=80-l2=1e-05	0.239
GNRRW-epoch=25-lr=0.00889-batch_size=256-embedding_size=128-l2=1e-05	0.202
GNRRW-epoch=30-lr=0.00889-batch_size=32-embedding_size=80-l2=1e-05	0.246
GNRRW-epoch=15-lr=0.00445-batch_size=64-embedding_size=200-l2=1e-05	0.203
GNRRW-epoch=25-lr=0.00889-batch_size=256-embedding_size=128-l2=3e-05	0.207
GNRRW-epoch=15-lr=0.00556-batch_size=256-embedding_size=200-l2=3e-05	0.207
GNRRW-epoch=30-lr=0.00112-batch_size=128-embedding_size=200-l2=3e-05	0.226
GNRRW-epoch=25-lr=0.00667-batch_size=100-embedding_size=200-l2=1e-05	0.215
GNRRW-epoch=15-lr=0.00556-batch_size=64-embedding_size=100-l2=1e-05	0.227
GNRRW-epoch=30-lr=0.00889-batch_size=128-embedding_size=200-l2=3e-05	0.225
GNRRW-epoch=15-lr=0.01-batch_size=256-embedding_size=128-l2=3e-05	0.225
GNRRW-epoch=30-lr=0.00778-batch_size=32-embedding_size=80-l2=1e-05	0.216
GNRRW-epoch=25-lr=0.00334-batch_size=64-embedding_size=80-l2=3e-05	0.223
GNRRW-epoch=25-lr=1e-05-batch_size=256-embedding_size=80-l2=3e-05	0.059
GNRRW-epoch=15-lr=0.00556-batch_size=100-embedding_size=128-l2=3e-05	0.225
GNRRW-epoch=30-lr=0.00112-batch_size=64-embedding_size=200-l2=1e-05	0.241
GNRRW-epoch=15-lr=0.01-batch_size=200-embedding_size=100-l2=3e-05	0.216
GNRRW-epoch=15-lr=0.00445-batch_size=256-embedding_size=80-l2=1e-05	0.257
GNRRW-epoch=30-lr=0.00223-batch_size=100-embedding_size=200-l2=1e-05	0.204
GNRRW-epoch=30-lr=0.00334-batch_size=200-embedding_size=200-l2=1e-05	0.222
GNRRW-epoch=25-lr=0.00556-batch_size=64-embedding_size=80-l2=1e-05	0.211
GNRRW-epoch=20-lr=0.00445-batch_size=128-embedding_size=80-l2=3e-05	0.238
GNRRW-epoch=30-lr=0.00667-batch_size=64-embedding_size=80-l2=1e-05	0.231
GNRRW-epoch=30-lr=0.00556-batch_size=100-embedding_size=200-l2=1e-05	0.195
GNRRW-epoch=25-lr=0.00667-batch_size=256-embedding_size=100-l2=3e-05	0.226
GNRRW-epoch=15-lr=0.01-batch_size=64-embedding_size=100-l2=3e-05	0.241
GNRRW-epoch=30-lr=0.00667-batch_size=64-embedding_size=80-l2=3e-05	0.251
GNRRW-epoch=15-lr=0.00334-batch_size=100-embedding_size=200-l2=1e-05	0.218
GNRRW-epoch=25-lr=0.00445-batch_size=256-embedding_size=100-l2=1e-05	0.255
GNRRW-epoch=15-lr=0.00445-batch_size=100-embedding_size=200-l2=3e-05	0.205
GNRRW-epoch=15-lr=0.00889-batch_size=256-embedding_size=100-l2=1e-05	0.222
GNRRW-epoch=25-lr=1e-05-batch_size=128-embedding_size=100-l2=1e-05	0.071
GNRRW-epoch=30-lr=0.00445-batch_size=200-embedding_size=128-l2=1e-05	0.226
GNRRW-epoch=20-lr=1e-05-batch_size=64-embedding_size=80-l2=1e-05	0.151
GNRRW-epoch=15-lr=0.00112-batch_size=200-embedding_size=200-l2=1e-05	0.233
GNRRW-epoch=30-lr=0.00445-batch_size=100-embedding_size=200-l2=3e-05	0.205
GNRRW-epoch=25-lr=0.00445-batch_size=128-embedding_size=80-l2=1e-05	0.233
GNRRW-epoch=30-lr=0.00778-batch_size=64-embedding_size=200-l2=1e-05	0.224
GNRRW-epoch=15-lr=0.01-batch_size=256-embedding_size=100-l2=1e-05	0.233
GNRRW-epoch=20-lr=0.00667-batch_size=128-embedding_size=100-l2=3e-05	0.233
GNRRW-epoch=30-lr=0.00778-batch_size=100-embedding_size=200-l2=3e-05	0.215
GNRRW-epoch=20-lr=1e-05-batch_size=32-embedding_size=100-l2=1e-05	0.165
GNRRW-epoch=15-lr=0.00334-batch_size=32-embedding_size=80-l2=3e-05	0.243
GNRRW-epoch=30-lr=0.00223-batch_size=128-embedding_size=200-l2=1e-05	0.234
GNRRW-epoch=20-lr=0.00667-batch_size=256-embedding_size=200-l2=1e-05	0.203
GNRRW-epoch=25-lr=0.00667-batch_size=32-embedding_size=200-l2=1e-05	0.231
GNRRW-epoch=20-lr=0.00334-batch_size=32-embedding_size=100-l2=3e-05	0.212
GNRRW-epoch=25-lr=0.00556-batch_size=256-embedding_size=128-l2=1e-05	0.208
GNRRW-epoch=30-lr=0.00445-batch_size=128-embedding_size=80-l2=1e-05	0.233

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.493
• Standard deviation: 0.034
• Maximum value: 0.543
• Minimum value: 0.413

Parameters/Matrics	MRR@20
GNRRW-epoch=15-lr=1e-04-batch_size=128-embedding_size=128-l2=0.01	0.503
GNRRW-epoch=20-lr=1e-04-batch_size=32-embedding_size=32-l2=1e-06	0.493
GNRRW-epoch=15-lr=0.0023-batch_size=20-embedding_size=16-l2=1e-06	0.448
GNRRW-epoch=10-lr=1e-04-batch_size=128-embedding_size=128-l2=0.01	0.504
GNRRW-epoch=10-lr=0.0012-batch_size=20-embedding_size=32-l2=0.0001	0.488
GNRRW-epoch=15-lr=0.0067-batch_size=32-embedding_size=32-l2=0.0001	0.478
GNRRW-epoch=10-lr=0.0012-batch_size=200-embedding_size=128-l2=0.0001	0.547
GNRRW-epoch=20-lr=1e-04-batch_size=200-embedding_size=200-l2=0.0001	0.590
GNRRW-epoch=10-lr=1e-04-batch_size=32-embedding_size=16-l2=1e-05	0.443
GNRRW-epoch=15-lr=1e-04-batch_size=200-embedding_size=128-l2=0.0001	0.531
GNRRW-epoch=20-lr=0.0045-batch_size=32-embedding_size=32-l2=0.01	0.454
GNRRW-epoch=5-lr=0.01-batch_size=128-embedding_size=64-l2=1e-06	0.525
GNRRW-epoch=10-lr=1e-04-batch_size=128-embedding_size=32-l2=0.0001	0.532
GNRRW-epoch=20-lr=0.0089-batch_size=20-embedding_size=128-l2=0.0001	0.462
GNRRW-epoch=10-lr=0.0056-batch_size=128-embedding_size=16-l2=0.01	0.429
GNRRW-epoch=15-lr=1e-04-batch_size=200-embedding_size=128-l2=0.0001	0.534
GNRRW-epoch=20-lr=0.0078-batch_size=100-embedding_size=16-l2=0.0001	0.465
GNRRW-epoch=15-lr=0.01-batch_size=200-embedding_size=128-l2=1e-06	0.534
GNRRW-epoch=20-lr=0.0056-batch_size=200-embedding_size=128-l2=1e-05	0.518
GNRRW-epoch=15-lr=0.0034-batch_size=100-embedding_size=16-l2=0.01	0.435
GNRRW-epoch=10-lr=0.0012-batch_size=32-embedding_size=32-l2=1e-06	0.512
GNRRW-epoch=10-lr=0.0034-batch_size=128-embedding_size=32-l2=0.0001	0.507
GNRRW-epoch=10-lr=0.01-batch_size=200-embedding_size=16-l2=0.0001	0.482
GNRRW-epoch=15-lr=0.0023-batch_size=32-embedding_size=16-l2=0.0001	0.460
GNRRW-epoch=10-lr=0.0012-batch_size=32-embedding_size=16-l2=0.0001	0.479
GNRRW-epoch=10-lr=0.01-batch_size=32-embedding_size=128-l2=0.01	0.442
GNRRW-epoch=10-lr=0.0089-batch_size=20-embedding_size=16-l2=1e-05	0.455
GNRRW-epoch=15-lr=0.01-batch_size=128-embedding_size=64-l2=1e-06	0.526
GNRRW-epoch=10-lr=0.0067-batch_size=128-embedding_size=16-l2=1e-05	0.497
GNRRW-epoch=15-lr=0.0078-batch_size=20-embedding_size=200-l2=1e-06	0.436
GNRRW-epoch=15-lr=0.0078-batch_size=200-embedding_size=32-l2=1e-05	0.514
GNRRW-epoch=10-lr=0.0012-batch_size=100-embedding_size=128-l2=0.01	0.482
GNRRW-epoch=15-lr=0.0056-batch_size=200-embedding_size=32-l2=0.01	0.460
GNRRW-epoch=10-lr=1e-04-batch_size=128-embedding_size=128-l2=1e-05	0.516
GNRRW-epoch=20-lr=0.0045-batch_size=100-embedding_size=32-l2=0.01	0.453
GNRRW-epoch=15-lr=0.0012-batch_size=128-embedding_size=16-l2=1e-06	0.543
GNRRW-epoch=10-lr=0.0078-batch_size=200-embedding_size=32-l2=0.01	0.468
GNRRW-epoch=20-lr=0.0067-batch_size=128-embedding_size=200-l2=0.0001	0.495
GNRRW-epoch=15-lr=0.0078-batch_size=32-embedding_size=128-l2=1e-06	0.488
GNRRW-epoch=10-lr=0.0089-batch_size=128-embedding_size=200-l2=1e-06	0.510
GNRRW-epoch=15-lr=1e-04-batch_size=20-embedding_size=16-l2=0.0001	0.413
GNRRW-epoch=20-lr=0.0089-batch_size=200-embedding_size=64-l2=0.01	0.463
GNRRW-epoch=15-lr=0.0078-batch_size=200-embedding_size=64-l2=0.0001	0.497
GNRRW-epoch=20-lr=0.01-batch_size=100-embedding_size=16-l2=0.0001	0.459
GNRRW-epoch=10-lr=0.0045-batch_size=128-embedding_size=200-l2=0.0001	0.507
GNRRW-epoch=20-lr=0.0089-batch_size=200-embedding_size=200-l2=0.0001	0.491
GNRRW-epoch=15-lr=0.0089-batch_size=128-embedding_size=16-l2=1e-06	0.526
GNRRW-epoch=20-lr=0.0089-batch_size=100-embedding_size=200-l2=0.01	0.450
GNRRW-epoch=10-lr=1e-04-batch_size=100-embedding_size=32-l2=1e-05	0.530
GNRRW-epoch=15-lr=1e-04-batch_size=100-embedding_size=128-l2=1e-06	0.524
GNRRW-epoch=10-lr=0.0045-batch_size=200-embedding_size=16-l2=1e-06	0.543
GNRRW-epoch=15-lr=1e-04-batch_size=128-embedding_size=64-l2=1e-06	0.527

Hyperparameters for TAGNN

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rate	[0.01 to 0.0001]
Batch Size	[20, 32, 100, 128, 200]
Embedding_size	[50, 100, 150]
L2 Penality	[0.00001, 0.0001]
Epoch	[10, 15, 20, 20, 25]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.261
• Standard deviation: 0.070
• Maximum value: 0.351
• Minimum value: 0.063

Parameters/Metrics	MRR@20
TAGNN-epoch=10-lr=0.005-batch_size=32-embedding_size=150-l2=0.0001	0.126
TAGNN-epoch=15-lr=0.0002-batch_size=100-embedding_size=100-l2=1e-05	0.315
TAGNN-epoch=10-lr=0.008-batch_size=100-embedding_size=100-l2=1e-05	0.279
TAGNN-epoch=10-lr=0.007-batch_size=128-embedding_size=150-l2=0.0001	0.211
TAGNN-epoch=10-lr=0.003-batch_size=100-embedding_size=100-l2=1e-05	0.317
TAGNN-epoch=15-lr=0.0009-batch_size=32-embedding_size=150-l2=0.0001	0.229
TAGNN-epoch=10-lr=0.007-batch_size=32-embedding_size=150-l2=0.0001	0.156
TAGNN-epoch=15-lr=0.0003-batch_size=20-embedding_size=100-l2=1e-05	0.317
TAGNN-epoch=15-lr=0.001-batch_size=20-embedding_size=100-l2=1e-05	0.311
TAGNN-epoch=10-lr=0.0008-batch_size=32-embedding_size=150-l2=1e-05	0.282
TAGNN-epoch=15-lr=0.006-batch_size=32-embedding_size=100-l2=0.0001	0.130
TAGNN-epoch=20-lr=0.005-batch_size=200-embedding_size=100-l2=0.0001	0.241
TAGNN-epoch=20-lr=0.0003-batch_size=128-embedding_size=100-l2=1e-05	0.321
TAGNN-epoch=20-lr=0.009-batch_size=200-embedding_size=100-l2=0.0001	0.180
TAGNN-epoch=15-lr=0.0008-batch_size=20-embedding_size=100-l2=0.0001	0.231
TAGNN-epoch=20-lr=0.009-batch_size=20-embedding_size=100-l2=1e-05	0.229
TAGNN-epoch=15-lr=0.01-batch_size=100-embedding_size=150-l2=0.0001	0.180
TAGNN-epoch=10-lr=0.002-batch_size=128-embedding_size=150-l2=0.0001	0.261
TAGNN-epoch=15-lr=0.003-batch_size=128-embedding_size=100-l2=0.0001	0.234
TAGNN-epoch=20-lr=0.004-batch_size=20-embedding_size=150-l2=1e-05	0.260
TAGNN-epoch=15-Lr=0.01-batch_size=100-embedding_size=100-l2=1e-05	0.275
TAGNN-epoch=20-lr=0.0006-batch_size=100-embedding_size=150-l2=0.0001	0.251
TAGNN-epoch=15-lr=0.0008-batch_size=128-embedding_size=100-l2=1e-05	0.333
TAGNN-epoch=15-lr=0.009-batch_size=100-embedding_size=150-l2=1e-05	0.267
TAGNN-epoch=10-lr=0.0009-batch_size=128-embedding_size=100-l2=1e-05	0.334
TAGNN-epoch=15-lr=0.007-batch_size=32-embedding_size=100-l2=0.0001	0.128
TAGNN-epoch=10-lr=0.0005-batch_size=20-embedding_size=100-l2=1e-05	0.309
TAGNN-epoch=15-lr=0.0002-batch_size=100-embedding_size=150-l2=1e-05	0.313
TAGNN-epoch=10-lr=0.006-batch_size=32-embedding_size=150-l2=0.0001	0.156
TAGNN-epoch=20-lr=0.001-batch_size=20-embedding_size=150-l2=1e-05	0.292
TAGNN-epoch=25-lr=0.0007-batch_size=100-embedding_size=100-l2=1e-05	0.351
TAGNN-epoch=10-lr=0.0004-batch_size=100-embedding_size=100-l2=1e-05	0.322
TAGNN-epoch=15-lr=0.01-batch_size=32-embedding_size=150-l2=1e-05	0.215
TAGNN-epoch=10-lr=1e-04-batch_size=32-embedding_size=150-l2=0.0001	0.252
TAGNN-epoch=15-lr=0.0008-batch_size=100-embedding_size=150-l2=1e-05	0.336
TAGNN-epoch=20-lr=1e-04-batch_size=100-embedding_size=150-l2=1e-05	0.317
TAGNN-epoch=10-lr=0.0005-batch_size=128-embedding_size=100-l2=1e-05	0.323
TAGNN-epoch=15-lr=0.0007-batch_size=128-embedding_size=150-l2=1e-05	0.319
TAGNN-epoch=20-lr=0.0006-batch_size=200-embedding_size=100-l2=0.0001	0.307
TAGNN-epoch=15-lr=0.01-batch_size=20-embedding_size=150-l2=0.0001	0.063
TAGNN-epoch=20-lr=0.008-batch_size=20-embedding_size=100-l2=0.0001	0.137
TAGNN-epoch=15-lr=0.001-batch_size=100-embedding_size=150-l2=1e-05	0.317
TAGNN-epoch=10-lr=0.005-batch_size=100-embedding_size=150-l2=1e-05	0.309
TAGNN-epoch=15-lr=0.001-batch_size=32-embedding_size=100-l2=0.0001	0.249
TAGNN-epoch=10-lr=0.0002-batch_size=32-embedding_size=150-l2=1e-05	0.333
TAGNN-epoch=15-lr=0.0007-batch_size=20-embedding_size=100-l2=1e-05	0.331
TAGNN-epoch=25-lr=0.001-batch_size=32-embedding_size=150-l2=1e-05	0.299
TAGNN-epoch=15-lr=0.005-batch_size=100-embedding_size=150-l2=0.0001	0.209
TAGNN-epoch=20-lr=1e-04-batch_size=100-embedding_size=100-l2=1e-05	0.320

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.285
• Standard deviation: 0.028
• Maximum value: 0.322
• Minimum value: 0.216

Parameters/Metrics	MRR@20
TAGNN-epoch=20-Lr=0.009-batch_size=32-embedding_size=100-l2=0.0001	0.235
TAGNN-epoch=20-lr=0.008-batch_size=128-embedding_size=150-l2=0.0001	0.256
TAGNN-epoch=20-lr=0.004-batch_size=128-embedding_size=150-l2=0.0001	0.294
TAGNN-epoch=20-lr=1e-04-batch_size=128-embedding_size=150-l2=1e-05	0.307
TAGNN-epoch=10-lr=0.01-batch_size=100-embedding_size=100-l2=0.0001	0.282
TAGNN-epoch=10-lr=0.0005-batch_size=32-embedding_size=100-l2=0.0001	0.308
TAGNN-epoch=15-lr=0.002-batch_size=32-embedding_size=150-l2=0.0001	0.274
TAGNN-epoch=25-lr=0.007-batch_size=32-embedding_size=100-l2=1e-05	0.278
TAGNN-epoch=15-lr=0.005-batch_size=20-embedding_size=150-l2=0.0001	0.231
TAGNN-epoch=25-lr=0.0004-batch_size=20-embedding_size=100-l2=1e-05	0.300
TAGNN-epoch=10-lr=0.0002-batch_size=100-embedding_size=150-l2=1e-05	0.315
TAGNN-epoch=15-lr=0.0003-batch_size=20-embedding_size=100-l2=0.0001	0.281
TAGNN-epoch=10-lr=0.0004-batch_size=20-embedding_size=100-l2=1e-05	0.313
TAGNN-epoch=15-lr=0.001-batch_size=128-embedding_size=150-l2=0.0001	0.322
TAGNN-epoch=25-lr=0.001-batch_size=100-embedding_size=100-l2=1e-05	0.312
TAGNN-epoch=15-lr=0.001-batch_size=128-embedding_size=150-l2=1e-05	0.320
TAGNN-epoch=25-lr=0.008-batch_size=32-embedding_size=100-l2=0.0001	0.254
TAGNN-epoch=10-lr=0.01-batch_size=20-embedding_size=100-l2=1e-05	0.239
TAGNN-epoch=20-lr=0.002-batch_size=128-embedding_size=150-l2=1e-05	0.310
TAGNN-epoch=10-lr=0.001-batch_size=128-embedding_size=100-l2=0.0001	0.303
TAGNN-epoch=15-lr=0.0008-batch_size=20-embedding_size=100-l2=0.0001	0.280
TAGNN-epoch=25-lr=0.009-batch_size=32-embedding_size=150-l2=1e-05	0.240
TAGNN-epoch=10-lr=0.0004-batch_size=32-embedding_size=100-l2=0.0001	0.293
TAGNN-epoch=25-lr=0.001-batch_size=128-embedding_size=100-l2=1e-05	0.321
TAGNN-epoch=10-lr=0.0007-batch_size=100-embedding_size=100-l2=0.0001	0.305
TAGNN-epoch=15-lr=0.008-batch_size=128-embedding_size=150-l2=1e-05	0.269
TAGNN-epoch=10-lr=0.0003-batch_size=100-embedding_size=100-l2=0.0001	0.300
TAGNN-epoch=20-lr=1e-04-batch_size=128-embedding_size=100-l2=1e-05	0.293
TAGNN-epoch=15-lr=0.0005-batch_size=100-embedding_size=100-l2=0.0001	0.302
TAGNN-epoch=20-lr=0.005-batch_size=128-embedding_size=100-l2=1e-05	0.310
TAGNN-epoch=20-lr=0.007-batch_size=128-embedding_size=150-l2=1e-05	0.272
TAGNN-epoch=20-lr=0.005-batch_size=128-embedding_size=150-l2=1e-05	0.306
TAGNN-epoch=15-lr=0.001-batch_size=32-embedding_size=100-l2=0.0001	0.297
TAGNN-epoch=20-lr=1e-04-batch_size=200-embedding_size=150-l2=0.0001	0.275
TAGNN-epoch=25-lr=0.006-batch_size=20-embedding_size=150-l2=0.0001	0.253
TAGNN-epoch=15-lr=0.003-batch_size=20-embedding_size=100-l2=0.0001	0.267
TAGNN-epoch=25-lr=0.009-batch_size=32-embedding_size=150-l2=0.0001	0.232
TAGNN-epoch=10-lr=0.0002-batch_size=128-embedding_size=150-l2=0.0001	0.282
TAGNN-epoch=15-lr=0.009-batch_size=20-embedding_size=100-l2=0.0001	0.216
TAGNN-epoch=15-lr=0.0006-batch_size=20-embedding_size=100-l2=1e-05	0.309
TAGNN-epoch=20-lr=0.0007-batch_size=100-embedding_size=100-l2=1e-05	0.307
TAGNN-epoch=15-lr=0.007-batch_size=20-embedding_size=100-l2=0.0001	0.239
TAGNN-epoch=20-lr=0.004-batch_size=128-embedding_size=100-l2=0.0001	0.308
TAGNN-epoch=15-lr=0.008-batch_size=200-embedding_size=100-l2=0.0001	0.285
TAGNN-epoch=10-lr=0.01-batch_size=20-embedding_size=100-l2=1e-05	0.234
TAGNN-epoch=15-lr=0.01-batch_size=200-embedding_size=100-l2=1e-05	0.294
TAGNN-epoch=25-lr=0.0005-batch_size=100-embedding_size=150-l2=1e-05	0.307
TAGNN-epoch=20-lr=0.0004-batch_size=100-embedding_size=150-l2=1e-05	0.295
TAGNN-epoch=10-lr=0.003-batch_size=128-embedding_size=100-l2=1e-05	0.316

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.381
• Standard deviation: 0.085
• Maximum value: 0.522
• Minimum value: 0.193

Parameters/Metrics	MRR@20
TAGNN-epoch=20-lr=0.0003-batch_size=20-embedding_size=150-l2=0.0001	0.257
TAGNN-epoch=20-lr=0.002-batch_size=128-embedding_size=100-l2=0.0001	0.380
TAGNN-epoch=20-lr=0.005-batch_size=100-embedding_size=100-l2=1e-05	0.418
TAGNN-epoch=20-lr=0.0004-batch_size=200-embedding_size=100-l2=0.0001	0.382
TAGNN-epoch=20-lr=0.005-batch_size=100-embedding_size=150-l2=1e-05	0.402
TAGNN-epoch=20-lr=0.005-batch_size=100-embedding_size=100-l2=1e-05	0.406
TAGNN-epoch=20-lr=0.008-batch_size=200-embedding_size=100-l2=1e-05	0.400
TAGNN-epoch=20-lr=0.002-batch_size=32-embedding_size=100-l2=0.0001	0.312
TAGNN-epoch=25-lr=0.008-batch_size=128-embedding_size=100-l2=1e-05	0.380
TAGNN-epoch=25-lr=0.003-batch_size=32-embedding_size=130-l2=0.0001	0.263
TAGNN-epoch=25-lr=0.003-batch_size=128-embedding_size=80-l2=0.0001	0.337
TAGNN-epoch=15-lr=0.0007-batch_size=32-embedding_size=100-l2=5e-05	0.388
TAGNN-epoch=15-lr=0.0006-batch_size=20-embedding_size=100-l2=5e-05	0.340
TAGNN-epoch=15-lr=0.0007-batch_size=100-embedding_size=100-l2=0.0001	0.388
TAGNN-epoch=20-lr=0.0004-batch_size=20-embedding_size=150-l2=3e-05	0.401
TAGNN-epoch=10-lr=0.0005-batch_size=32-embedding_size=150-l2=3e-05	0.456
TAGNN-epoch=15-lr=0.0008-batch_size=20-embedding_size=150-l2=5e-05	0.326
TAGNN-epoch=20-lr=0.001-batch_size=32-embedding_size=150-l2=0.0001	0.292
TAGNN-epoch=10-lr=0.0008-batch_size=20-embedding_size=150-l2=1e-05	0.471
TAGNN-epoch=15-lr=0.007-batch_size=20-embedding_size=100-l2=5e-05	0.193
TAGNN-epoch=15-lr=0.0005-batch_size=32-embedding_size=150-l2=0.0001	0.295
TAGNN-epoch=20-lr=0.0007-batch_size=32-embedding_size=100-l2=1e-05	0.481
TAGNN-epoch=15-lr=0.0007-batch_size=32-embedding_size=100-l2=5e-05	0.388
TAGNN-epoch=10-lr=0.0006-batch_size=128-embedding_size=150-l2=1e-05	0.510
TAGNN-epoch=20-lr=0.001-batch_size=100-embedding_size=150-l2=1e-05	0.501
TAGNN-epoch=10-lr=0.0002-batch_size=100-embedding_size=100-l2=1e-05	0.522
TAGNN-epoch=10-lr=0.001-batch_size=32-embedding_size=100-l2=1e-05	0.450
TAGNN-epoch=25-lr=0.0006-batch_size=32-embedding_size=100-l2=0.0001	0.299
TAGNN-epoch=20-lr=0.001-batch_size=200-embedding_size=100-l2=1e-05	0.512
TAGNN-epoch=15-lr=0.0002-batch_size=20-embedding_size=150-l2=0.0001	0.270

Hyperparameters for COTREC

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rate	[0.01 to 0.0001]
Batch Size	[20, 32, 64, 100, 128, 256, 512, 50]
Embedding Size	[20, 50, 64, 100, 120, 200]
L2 Penality	[0.00001, 0.0001]
Dropout	[0, 0.1, 0.2, 0.4, 0.5, 0.6]
Epoch	[10, 15, 20]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.361
• Standard deviation: 0.048
• Maximum value: 0.385
• Minimum value: 0.145

Parameters/Metrics	MRR@20
COTREC-epoch:15-lr=0.007-batch_size=64-embedding_size:100-l2=0.0001	0.373
COTREC-epoch=20-lr=0.003-batch_size=200-embedding_size=20-L2=0.0001	0.359
COTREC-epoch=10-lr=0.003-batch_size=200-embedding_size=50-l2=0.0001	0.372
COTREC-epoch=15-lr=0.009-batch_size=128-embedding_size=50-l2=1e-05	0.381
COTREC-epoch=10-lr=0.0008-batch_size=128-embedding_size=20-l2=0.0001	0.346
COTREC-epoch=15-lr=0.0003-batch_size=64-embedding_size=20-l2=1e-05	0.347
COTREC-epoch=10-lr=0.002-batch_size=200-embedding_size=20-l2=1e-05	0.353
COTREC-epoch=15-lr=0.0004-batch_size=128-embedding_size=20-l2=0.0001	0.346
COTREC-epoch=10-lr=0.0001-batch_size=64-embedding_size=200-l2=1e-05;	0.145
COTREC-epoch=10-lr=0.001-batch_size=64-embedding_size=200-l2=1e-05	0.384
COTREC-epoch=15-lr=0.0002-batch_size=200-embedding_size=100-l2=0.000	0.375
COTREC-epoch=15-lr=0.003-batch_size=64-embedding_size=50-l2=1e-05	0.379
COTREC-epoch=10-lr=0.009-batch_size=64-embedding_size=100-l2=0.0001	0.378
COTREC-epoch=20-lr=0.001-batch_size=128-embedding_size=100-l2=0.0001	0.378
COTREC-epoch=20-lr=0.003-batch_size=200-embedding_size=100-l2=0.0001	0.380
COTREC-epoch=20-lr=0.0007-batch_size=256-embedding_size=128-l2=0.0003	0.380
COTREC-epoch=10-lr=0.0004-batch_size=100-embedding_size=64-l2=0.0003	0.369
COTREC-epoch=20-lr=0.009-batch_size=80-embedding_size=50-l2=1e-05	0.382
COTREC-epoch=10-lr=0.007-batch_size=64-embedding_size=64-l2=0.0003	0.381
COTREC-epoch=15-lr=0.0005-batch_size=256-embedding_size=64-l2=1e-05	0.369
COTREC-epoch=20-lr=0.002-batch_size=128-embedding_size=80-l2=4e-05	0.373
COTREC-epoch=20-lr=0.0009-batch_size=50-embedding_size=64-l2=0.0003	0.385
COTREC-epoch=15-lr=0.007-batch_size=128-embedding_size=64-l2=0.0003	0.381

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.277
• Standard deviation: 0.003
• Maximum value: 0.284
• Minimum value: 0.268

Parameters/Metrics	MRR@20
COTREC-epoch=20-lr=0.005-batch_size=50-embedding_size=50-l2=4e-05	0.275
COTREC-epoch=10-lr=0.004-batch_size=50-embedding_size=64-l2=4e-05	0.273
COTREC-epoch=15-lr=0.005-batch_size=50-embedding_size=100-l2=0.0003	0.274
COTREC-epoch=20-lr=0.0009-batch_size=80-embedding_size=128-l2=0.0003	0.276
COTREC-epoch=20-lr=0.003-batch_size=64-embedding_size=128-l2=0.0003	0.278
COTREC-epoch=10-lr=0.0007-batch_size=256-embedding_size=100-l2=0.0003	0.279
COTREC-epoch=10-lr=1e-04-batch_size=80-embedding_size=50-l2=0.0003	0.268
COTREC-epoch=20-lr=0.003-batch_size=50-embedding_size=80-l2=4e-05	0.283
COTREC-epoch=15-lr=0.0002-batch_size=32-embedding_size=128-l2=1e-05	0.277
COTREC-epoch=10-lr=0.004-batch_size=80-embedding_size=64-l2=1e-05	0.274
COTREC-epoch=10-lr=0.008-batch_size=256-embedding_size=100-l2=0.0003	0.274
COTREC-epoch=15-lr=0.001-batch_size=80-embedding_size=50-l2=0.0001	0.275
COTREC-epoch=15-lr=0.001-batch_size=50-embedding_size=64-l2=0.0001	0.281
COTREC-epoch=15-lr=0.01-batch_size=256-embedding_size=128-l2=0.0003	0.284
COTREC-epoch=10-lr=0.008-batch_size=100-embedding_size=128-l2=0.0003	0.278
COTREC-epoch=15-lr=0.001-batch_size=80-embedding_size=64-l2=4e-05	0.276
COTREC-epoch=15-lr=0.01-batch_size=50-embedding_size=128-l2=1e-05	0.274
COTREC-epoch=15-lr=0.0008-batch_size=80-embedding_size=100-l2=0.0001	0.281
COTREC-epoch=15-lr=0.0003-batch_size=64-embedding_size=80-l2=1e-05	0.281
COTREC-epoch=15-lr=0.005-batch_size=256-embedding_size=80-l2=1e-05	0.275
COTREC-epoch=20-lr=0.008-batch_size=100-embedding_size=80-l2=0.0001	0.278
COTREC-epoch=15-lr=0.0006-batch_size=80-embedding_size=80-l2=1e-05	0.280
COTREC-epoch=10-lr=1e-04-batch_size=128-embedding_size=128-l2=1e-05	0.276
COTREC-epoch=15-lr=0.0008-batch_size=32-embedding_size=80-l2=4e-05	0.279
COTREC-epoch=20-lr=0.0008-batch_size=80-embedding_size=64-l2=0.0003	0.281

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.514
• Standard deviation: 0.015
• Maximum value: 0.535
• Minimum value: 0.471

Parameters/Metrics	MRR@20
COTREC-epoch=15-lr=0.005-batch_size=256-embedding_size=120-l2=0.0001	0.523
COTREC-epoch=15-lr=0.0007-batch_size=256-embedding_size=150-l2=0.0003	0.521
COTREC-epoch=15-lr=0.0006-batch_size=512-embedding_size=200-l2=1e-05	0.520
COTREC-epoch=15-lr=0.005-batch_size=256-embedding_size=200-l2=0.0003	0.522
COTREC-epoch=15-lr=1e-04-batch_size=256-embedding_size=100-l2=1e-05	0.498
COTREC-epoch=15-lr=0.0007-batch_size=128-embedding_size=100-l2=0.0003	0.521
COTREC-epoch=15-lr=0.0005-batch_size=64-embedding_size=150-l2=0.0003	0.526
COTREC-epoch=15-lr=0.01-batch_size=128-embedding_size=100-l2=0.0003	0.514
COTREC-epoch=15-lr=0.0002-batch_size=256-embedding_size=200-l2=0.0003	0.514
COTREC-epoch=15-lr=0.01-batch_size=256-embedding_size=100-l2=1e-05	0.526
COTREC-epoch=20-lr=0.006-batch_size=20-embedding_size=80-l2=0.0001	0.495
COTREC-epoch=20-lr=0.001-batch_size=80-embedding_size=80-l2=0.0003	0.517
COTREC-epoch=20-lr=0.003-batch_size=100-embedding_size=80-l2=0.0001	0.535
COTREC-epoch=20-lr=0.0002-batch_size=100-embedding_size=50-l2=0.0001	0.507
COTREC-epoch=20-lr=0.001-batch_size=50-embedding_size=20-l2=0.0003	0.487
COTREC-epoch=20-lr=0.0002-batch_size=100-embedding_size=20-l2=1e-05	0.471
COTREC-epoch=20-lr=0.004-batch_size=80-embedding_size=50-l2=0.003	0.525
COTREC-epoch=20-lr=0.01-batch_size=20-embedding_size=100-l2=0.003	0.508
COTREC-epoch=20-lr=0.009-batch_size=100-embedding_size=20-l2=0.0001	0.484
COTREC-epoch=20-lr=0.001-batch_size=50-embedding_size=50-l2=1e-05	0.522
COTREC-epoch=10-lr=0.005-batch_size=128-embedding_size=64-l2=1e-05	0.515
COTREC-epoch=20-lr=0.0009-batch_size=80-embedding_size=80-l2=0.0003	0.523
COTREC-epoch=20-lr=0.0009-batch_size=64-embedding_size=64-l2=1e-05	0.526
COTREC-epoch=10-lr=0.007-batch_size=256-embedding_size=80-l2=0.0001	0.520
COTREC-epoch=20-lr=0.004-batch_size=80-embedding_size=128-l2=0.0001	0.531

Hyperparameters for FLCSP

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rate	[0.01 to 0.0001]
Batch Size	[20, 32, 100, 128, 200, 300, 256, 16, 250]
Embedding Size	[100, 250, 50, 100, 150, 200]
L2 Penality	[0.0001, 0.00001]
Dropout	[0.1,0.2,0.3, 0.4, 0.5]
Epoch	[10, 15, 20]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.103
• Standard deviation: 0.086
• Maximum value: 0.316
• Minimum value: 0.001

Parameters/Metrics	MRR@20
FLCSP_cate-epoch:15-Lr:0.002-batch_size:20-embedding_size:300-L2:1e-05-Dropout:0.2-hidden_size:50	0.226
FLCSP_cate-epoch:10-Lr:0.003-batch_size:200-embedding_size:200-L2:1e-06-Dropout:0.1-hidden_size:50	0.072
FLCSP_cate-epoch:10-Lr:0.0002-batch_size:300-embedding_size:150-L2:0.0001-Dropout:0.3-hidden_size:50	0.091
FLCSP_cate-epoch:15-Lr:0.002-batch_size:20-embedding_size:200-L2:1e-05-Dropout:0.2-hidden_size:50	0.158
FLCSP_cate-epoch:20-Lr:0.0005-batch_size:200-embedding_size:100-L2:0.0001-Dropout:0.3-hidden_size:50	0.219
FLCSP_cate-epoch:20-Lr:0.006-batch_size:32-embedding_size:250-L2:1e-05-Dropout:0.2-hidden_size:50	0.211
FLCSP_cate-epoch:15-Lr:0.003-batch_size:200-embedding_size:250-L2:1e-05-Dropout:0.2-hidden_size:50	0.093
FLCSP_cate-epoch:10-Lr:0.001-batch_size:128-embedding_size:150-L2:1e-06-Dropout:0.5-hidden_size:50	0.093
FLCSP_cate-epoch:15-Lr:0.0006-batch_size:100-embedding_size:150-L2:1e-05-Dropout:0.1-hidden_size:50	0.042
FLCSP_cate-epoch:15-Lr:1e-04-batch_size:128-embedding_size:150-L2:1e-05-Dropout:0.1-hidden_size:50	0.060
FLCSP_cate-epoch:10-Lr:0.008-batch_size:20-embedding_size:250-L2:1e-06-Dropout:0.4-hidden_size:50	0.153
FLCSP_cate-epoch:10-Lr:0.002-batch_size:20-embedding_size:200-L2:1e-05-Dropout:0.3-hidden_size:50	0.275
FLCSP_cate-epoch:10-Lr:0.0009-batch_size:300-embedding_size:250-L2:1e-05-Dropout:0.2-hidden_size:50	0.025
FLCSP_cate-epoch:20-Lr:0.004-batch_size:128-embedding_size:200-L2:0.0001-Dropout:0.1-hidden_size:50	0.019
FLCSP_cate-epoch:15-Lr:1e-04-batch_size:32-embedding_size:200-L2:1e-06-Dropout:0.3-hidden_size:50	0.001
FLCSP_cate-epoch:20-Lr:0.003-batch_size:128-embedding_size:150-L2:1e-06-Dropout:0.1-hidden_size:50	0.041
FLCSP_cate-epoch:15-Lr:0.0009-batch_size:128-embedding_size:300-L2:1e-05-Dropout:0.3-hidden_size:50	0.067
FLCSP_cate-epoch:20-Lr:0.0003-batch_size:300-embedding_size:150-L2:1e-06-Dropout:0.5-hidden_size:50	0.067
FLCSP_cate-epoch:10-Lr:0.002-batch_size:128-embedding_size:150-L2:1e-06-Dropout:0.2-hidden_size:50	0.040
FLCSP_cate-epoch:15-Lr:0.0002-batch_size:128-embedding_size:200-L2:1e-05-Dropout:0.5-hidden_size:50	0.011
FLCSP_cate-epoch:10-Lr:0.007-batch_size:100-embedding_size:150-L2:1e-06-Dropout:0.1-hidden_size:50	0.035
FLCSP_cate-epoch:15-Lr:0.0003-batch_size:200-embedding_size:250-L2:0.0001-Dropout:0.3-hidden_size:50	0.014
FLCSP_cate-epoch:10-Lr:0.009-batch_size:100-embedding_size:300-L2:1e-05-Dropout:0.1-hidden_size:50	0.012
FLCSP_cate-epoch:20-Lr:0.003-batch_size:128-embedding_size:300-L2:1e-06-Dropout:0.1-hidden_size:50	0.316
FLCSP_cate-epoch:20-Lr:0.001-batch_size:300-embedding_size:150-L2:0.0001-Dropout:0.1-hidden_size:50	0.083
FLCSP_cate-epoch:15-Lr:0.0009-batch_size:20-embedding_size:200-L2:0.0001-Dropout:0.3-hidden_size:50	0.139
FLCSP_cate-epoch:10-Lr:0.0007-batch_size:100-embedding_size:300-L2:1e-05-Dropout:0.2-hidden_size:50	0.027
FLCSP_cate-epoch:10-Lr:1e-04-batch_size:128-embedding_size:150-L2:0.0001-Dropout:0.5-hidden_size:50	0.087
FLCSP_cate-epoch:20-Lr:0.001-batch_size:128-embedding_size:250-L2:1e-05-Dropout:0.5-hidden_size:50	0.081
FLCSP_cate-epoch:20-Lr:0.0009-batch_size:32-embedding_size:250-L2:1e-05-Dropout:0.5-hidden_size:50	0.289
FLCSP_cate-epoch:10-Lr:0.0002-batch_size:128-embedding_size:300-L2:1e-06-Dropout:0.3-hidden_size:50	0.080
FLCSP_cate-epoch:15-Lr:1e-04-batch_size:200-embedding_size:150-L2:1e-06-Dropout:0.5-hidden_size:50	0.076
FLCSP_cate-epoch:20-Lr:0.004-batch_size:300-embedding_size:100-L2:1e-06-Dropout:0.2-hidden_size:50	0.014
FLCSP_cate-epoch:20-Lr:0.009-batch_size:128-embedding_size:100-L2:1e-06-Dropout:0.4-hidden_size:50	0.087
FLCSP_cate-epoch:15-Lr:0.005-batch_size:128-embedding_size:150-L2:1e-06-Dropout:0.5-hidden_size:50	0.142
FLCSP_cate-epoch:15-Lr:0.001-batch_size:100-embedding_size:150-L2:0.0001-Dropout:0.4-hidden_size:50	0.117
FLCSP_cate-epoch:20-Lr:0.0004-batch_size:20-embedding_size:200-L2:1e-05-Dropout:0.2-hidden_size:50	0.158
FLCSP_cate-epoch:20-Lr:0.0009-batch_size:128-embedding_size:200-L2:1e-05-Dropout:0.5-hidden_size:50	0.275
FLCSP_cate-epoch:10-Lr:0.001-batch_size:128-embedding_size:300-L2:0.0001-Dropout:0.2-hidden_size:50	0.028

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.035
• Standard deviation: 0.018
• Maximum value: 0.118
• Minimum value: 0.020

Parameters/Metrics	MRR@20
FLCSP_cate-epoch=15-lr=0.0009-batch_size=128-embedding_size=100-l2=1e-05-Dropout=0.2-hidden_size=50	0.023
FLCSP_cate-epoch=15-lr=0.004-batch_size=20-embedding_size=250-l2=0.0001-Dropout=0.1-hidden_size=50	0.019
FLCSP_cate-epoch=10-lr=0.0005-batch_size=128-embedding_size=150-l2=0.0001-Dropout=0.2-hidden_size=50	0.025
FLCSP_cate-epoch=15-lr=0.006-batch_size=32-embedding_size=300-l2=0.0001-Dropout=0.2-hidden_size=50	0.022
FLCSP_cate-epoch=10-lr=0.006-batch_size=128-embedding_size=200-l2=1e-06-Dropout=0.2-hidden_size=50	0.035
FLCSP_cate-epoch=15-lr=0.006-batch_size=200-embedding_size=300-l2=1e-05-Dropout=0.1-hidden_size=50	0.020
FLCSP_cate-epoch=10-lr=0.0007-batch_size=100-embedding_size=300-l2=1e-06-Dropout=0.2-hidden_size=50	0.023
FLCSP_cate-epoch=15-lr=0.006-batch_size=20-embedding_size=250-l2=1e-06-Dropout=0.1-hidden_size=50	0.025
FLCSP_cate-epoch=20-lr=0.0007-batch_size=20-embedding_size=200-l2=1e-06-Dropout=0.2-hidden_size=50	0.022
FLCSP_cate-epoch=15-lr=0.0009-batch_size=20-embedding_size=250-l2=1e-06-Dropout=0.4-hidden_size=50	0.037
FLCSP_cate-epoch=15-lr=0.01-batch_size=100-embedding_size=250-l2=1e-06-Dropout=0.2-hidden_size=50	0.029
FLCSP_cate-epoch=20-lr=0.005-batch_size=200-embedding_size=100-l2=1e-06-Dropout=0.5-hidden_size=50	0.029
FLCSP_cate-epoch=20-lr=1e-04-batch_size=128-embedding_size=250-l2=1e-06-Dropout=0.3-hidden_size=50	0.118
FLCSP_cate-epoch=15-lr=0.0007-batch_size=300-embedding_size=250-l2=0.0001-Dropout=0.4-hidden_size=50	0.035
FLCSP_cate-epoch=10-lr=0.0004-batch_size=200-embedding_size=100-l2=1e-05-Dropout=0.2-hidden_size=50	0.062
FLCSP_cate-epoch=20-lr=1e-04-batch_size=100-embedding_size=300-l2=1e-06-Dropout=0.2-hidden_size=50	0.118
FLCSP_cate-epoch=10-lr=0.008-batch_size=20-embedding_size=200-l2=1e-06-Dropout=0.3-hidden_size=50	0.034
FLCSP_cate-epoch=15-lr=0.01-batch_size=32-embedding_size=200-l2=0.0001-Dropout=0.5-hidden_size=50	0.022
FLCSP_cate-epoch=15-lr=0.01-batch_size=200-embedding_size=100-l2=1e-05-Dropout=0.2-hidden_size=50	0.034
FLCSP_cate-epoch=10-lr=0.0007-batch_size=100-embedding_size=300-l2=0.0001-Dropout=0.2-hidden_size=50	0.035
FLCSP_cate-epoch=10-lr=0.004-batch_size=100-embedding_size=200-l2=1e-05-Dropout=0.3-hidden_size=50	0.027
FLCSP_cate-epoch=10-lr=0.005-batch_size=128-embedding_size=100-l2=1e-06-Dropout=0.1-hidden_size=50	0.044
FLCSP_cate-epoch=10-lr=0.005-batch_size=300-embedding_size=250-l2=1e-05-Dropout=0.1-hidden_size=500	0.035
FLCSP_cate-epoch=20-lr=0.003-batch_size=100-embedding_size=150-l2=0.0001-Dropout=0.2-hidden_size=50	0.035
FLCSP_cate-epoch=15-lr=0.003-batch_size=200-embedding_size=200-l2=1e-06-Dropout=0.3-hidden_size=50	0.025
FLCSP_cate-epoch=20-lr=0.0009-batch_size=20-embedding_size=100-l2=1e-06-Dropout=0.5-hidden_size=50	0.060
FLCSP_cate-epoch=10-lr=0.01-batch_size=128-embedding_size=100-l2=0.0001-Dropout=0.2-hidden_size=50	0.025
FLCSP_cate-epoch=20-lr=0.003-batch_size=200-embedding_size=250-l2=1e-06-Dropout=0.2-hidden_size=51	0.021
FLCSP_cate-epoch=15-lr=1e-04-batch_size=200-embedding_size=150-l2=1e-05-Dropout=0.2-hidden_size=50	0.118
FLCSP_cate-epoch=15-lr=0.002-batch_size=300-embedding_size=250-l2=0.0001-Dropout=0.3-hidden_size=50	0.023
FLCSP_cate-epoch=10-lr=0.009-batch_size=300-embedding_size=100-l2=1e-06-Dropout=0.1-hidden_size=50	0.025
FLCSP_cate-epoch=10-lr=0.007-batch_size=100-embedding_size=250-l2=0.0001-Dropout=0.4-hidden_size=50	0.035
FLCSP_cate-epoch=10-lr=0.005-batch_size=32-embedding_size=100-l2=1e-05-Dropout=0.5-hidden_size=50	0.025
FLCSP_cate-epoch=20-lr=0.008-batch_size=200-embedding_size=250-l2=1e-06-Dropout=0.2-hidden_size=50	0.029
FLCSP_cate-epoch=15-lr=0.002-batch_size=100-embedding_size=250-l2=0.0001-Dropout=0.3-hidden_size=50	0.022
FLCSP_cate-epoch=15-lr=0.006-batch_size=200-embedding_size=250-l2=0.0001-Dropout=0.4-hidden_size=50	0.029
FLCSP_cate-epoch=10-lr=0.007-batch_size=200-embedding_size=300-l2=0.0001-Dropout=0.4-hidden_size=50	0.025
FLCSP_cate-epoch=15-lr=0.01-batch_size=20-embedding_size=300-l2=1e-05-Dropout=0.3-hidden_size=50	0.027
FLCSP_cate-epoch=15-lr=0.005-batch_size=128-embedding_size=100-l2=1e-05-Dropout=0.1-hidden_size=50	0.029
FLCSP_cate-epoch=15-lr=0.001-batch_size=32-embedding_size=150-l2=1e-05-Dropout=0.5-hidden_size=50	0.028
FLCSP_cate-epoch=10-lr=0.0006-batch_size=20-embedding_size=300-l2=0.0001-Dropout=0.4-hidden_size=50	0.020
FLCSP_cate-epoch=20-lr=1e-04-batch_size=128-embedding_size=200-l2=1e-05-Dropout=0.5-hidden_size=50	0.062
FLCSP_cate-epoch=10-lr=0.005-batch_size=20-embedding_size=200-l2=0.0001-Dropout=0.3-hidden_size=50	0.022
FLCSP_cate-epoch=10-lr=0.006-batch_size=300-embedding_size=300-l2=1e-06-Dropout=0.5-hidden_size=50	0.029
FLCSP_cate-epoch=15-lr=0.005-batch_size=300-embedding_size=200-l2=1e-06-Dropout=0.1-hidden_size=50	0.024
FLCSP_cate-epoch=10-lr=0.0005-batch_size=300-embedding_size=150-l2=1e-06-Dropout=0.2-hidden_size=50	0.118
FLCSP_cate-epoch=10-lr=0.0004-batch_size=300-embedding_size=250-l2=0.0001-Dropout=0.2-hidden_size=50	0.062
FLCSP_cate-epoch=15-lr=0.006-batch_size=100-embedding_size=100-l2=0.0001-Dropout=0.5-hidden_size=50	0.029
FLCSP_cate-epoch=1-lr=0.0003-batch_size=20-embedding_size=200-l2=1e-06-Dropout=0.1-hidden_size=50	0.044
FLCSP_cate-epoch=10-lr=0.007-batch_size=20-embedding_size=150-l2=0.0001-Dropout=0.5-hidden_size=50	0.022
FLCSP_cate-epoch=15-lr=0.0002-batch_size=32-embedding_size=300-l2=1e-05-Dropout=0.4-hidden_size=50	0.062
FLCSP_cate-epoch=15-lr=0.0003-batch_size=32-embedding_size=300-l2=1e-05-Dropout=0.5-hidden_size=50	0.034
FLCSP_cate-epoch=15-lr=0.0009-batch_size=200-embedding_size=200-l2=1e-06-Dropout=0.5-hidden_size=50	0.021
FLCSP_cate-epoch=10-lr=0.0005-batch_size=100-embedding_size=250-l2=0.0001-Dropout=0.3-hidden_size=50	0.027
FLCSP_cate-epoch=10-lr=0.003-batch_size=200-embedding_size=100-l2=1e-06-Dropout=0.2-hidden_size=50	0.031
FLCSP_cate-epoch=10-lr=0.0004-batch_size=20-embedding_size=200-l2=0.0001-Dropout=0.2-hidden_size=50	0.029
FLCSP_cate-epoch=15-lr=0.0008-batch_size=20-embedding_size=250-l2=1e-06-Dropout=0.2-hidden_size=50	0.034
FLCSP_cate-epoch=15-lr=0.002-batch_size=100-embedding_size=150-l2=1e-06-Dropout=0.1-hidden_size=50	0.023
FLCSP_cate-epoch=15-lr=0.004-batch_size=200-embedding_size=150-l2=0.0001-Dropout=0.3-hidden_size=50	0.029
FLCSP_cate-epoch=15-lr=0.002-batch_size=100-embedding_size=100-l2=1e-06-Dropout=0.3-hidden_size=50	0.029
FLCSP_cate-epoch=10-lr=0.009-batch_size=32-embedding_size=100-l2=1e-05-Dropout=0.5-hidden_size=50	0.022
FLCSP_cate-epoch=20-lr=1e-04-batch_size=128-embedding_size=100-l2=1e-05-Dropout=0.5-hidden_size=50	0.062
FLCSP_cate-epoch=10-lr=0.0005-batch_size=128-embedding_size=150-l2=1e-05-Dropout=0.5-hidden_size=50	0.029
FLCSP_cate-epoch=10-lr=0.001-batch_size=100-embedding_size=250-l2=1e-05-Dropout=0.3-hidden_size=50	0.025
FLCSP_cate-epoch=10-lr=0.0002-batch_size=200-embedding_size=250-l2=1e-05-Dropout=0.3-hidden_size=50	0.043
FLCSP_cate-epoch=15-lr=0.004-batch_size=300-embedding_size=250-l2=1e-05-Dropout=0.3-hidden_size=50	0.023
FLCSP_cate-epoch=20-lr=0.0004-batch_size=20-embedding_size=250-l2=0.0001-Dropout=0.5-hidden_size=50	0.035
FLCSP_cate-epoch=10-lr=0.0008-batch_size=300-embedding_size=150-l2=1e-06-Dropout=0.1-hidden_size=50	0.029
FLCSP_cate-epoch=20-lr=0.0002-batch_size=300-embedding_size=250-l2=1e-05-Dropout=0.1-hidden_size=50	0.062

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.238
• Standard deviation: 0.133
• Maximum value: 0.459
• Minimum value: 0.048

Parameters/Metrics	MRR@20
FLCSP_cate-epoch=20-lr=0.0004-batch_size=256-embedding_size=100-hidden_size=150-dropout=0.2-l2=1e-05	0.421
FLCSP_cate-epoch=20-lr=0.002-batch_size=16-embedding_size=250-hidden_size=150-dropout=0.1-l2=1e-05	0.125
FLCSP_cate-epoch=20-lr=1e-04-batch_size=128-embedding_size=50-hidden_size=50-dropout=0.4-l2=1e-05	0.450
FLCSP_cate-epoch=20-lr=0.001-batch_size=16-embedding_size=200-hidden_size=150-dropout=0.5-l2=0.0001	0.083
FLCSP_cate-epoch=20-lr=0.0008-batch_size=64-embedding_size=200-hidden_size=250-dropout=0.4-l2=1e-05	0.321
FLCSP_cate-epoch=20-lr=0.006-batch_size=64-embedding_size=100-hidden_size=50-dropout=0.3-l2=1e-06	0.210
FLCSP_cate-epoch=20-lr=0.008-batch_size=64-embedding_size=150-hidden_size=250-dropout=0.4-l2=1e-05	0.146
FLCSP_cate-epoch=20-lr=0.0006-batch_size=64-embedding_size=150-hidden_size=250-dropout=0.4-l2=0.0001	0.249
FLCSP_cate-epoch=20-lr=0.0006-batch_size=256-embedding_size=250-hidden_size=200-dropout=0.1-l2=1e-05	0.446
FLCSP_cate-epoch=20-lr=0.004-batch_size=32-embedding_size=150-hidden_size=250-dropout=0.2-l2=0.0001	0.101
FLCSP_cate-epoch=20-lr=0.0007-batch_size=128-embedding_size=250-hidden_size=100-dropout=0.3-l2=1e-06	0.451
FLCSP_cate-epoch=20-lr=0.0002-batch_size=16-embedding_size=100-hidden_size=200-dropout=0.5-l2=1e-05	0.209
FLCSP_cate-epoch=20-lr=0.009-batch_size=128-embedding_size=150-hidden_size=100-dropout=0.3-l2=1e-05	0.186
FLCSP_cate-epoch=20-lr=0.01-batch_size=16-embedding_size=200-hidden_size=100-dropout=0.2-l2=0.0001	0.066
FLCSP_cate-epoch=20-lr=0.005-batch_size=256-embedding_size=250-hidden_size=50-dropout=0.1-l2=1e-06	0.325
FLCSP_cate-epoch=20-lr=1e-04-batch_size=128-embedding_size=200-hidden_size=150-dropout=0.2-l2=1e-05	0.459
FLCSP_cate-epoch=20-lr=0.007-batch_size=64-embedding_size=150-hidden_size=150-dropout=0.1-l2=1e-06	0.185
FLCSP_cate-epoch=20-lr=0.0002-batch_size=64-embedding_size=150-hidden_size=150-dropout=0.3-l2=1e-05	0.356
FLCSP_cate-epoch=20-lr=0.0006-batch_size=16-embedding_size=250-hidden_size=50-dropout=0.3-l2=0.0001	0.057
FLCSP_cate-epoch=20-lr=0.0007-batch_size=16-embedding_size=250-hidden_size=250-dropout=0.3-l2=0.0001	0.048
FLCSP_cate-epoch=20-lr=0.0005-batch_size=16-embedding_size=150-hidden_size=200-dropout=0.3-l2=1e-05	0.151
FLCSP_cate-epoch=20-lr=1e-04-batch_size=16-embedding_size=250-hidden_size=50-dropout=0.4-l2=0.0001	0.138
FLCSP_cate-epoch=20-lr=0.0009-batch_size=256-embedding_size=150-hidden_size=200-dropout=0.4-l2=1e-05	0.439
FLCSP_cate-epoch=20-lr=0.0008-batch_size=128-embedding_size=100-hidden_size=200-dropout=0.5-l2=0.0001	0.272
FLCSP_cate-epoch=20-lr=0.006-batch_size=256-embedding_size=150-hidden_size=150-dropout=0.3-l2=1e-06	0.321
FLCSP_cate-epoch=20-lr=1e-04-batch_size=16-embedding_size=50-hidden_size=250-dropout=0.5-l2=1e-05	0.251
FLCSP_cate-epoch=20-lr=0.0002-batch_size=32-embedding_size=250-hidden_size=100-dropout=0.5-l2=0.0001	0.182
FLCSP_cate-epoch=20-lr=0.007-batch_size=128-embedding_size=50-hidden_size=250-dropout=0.3-l2=0.0001	0.102
FLCSP_cate-epoch=20-lr=0.003-batch_size=16-embedding_size=50-hidden_size=250-dropout=0.4-l2=1e-06	0.129
FLCSP_cate-epoch=20-lr=0.001-batch_size=32-embedding_size=200-hidden_size=100-dropout=0.5-l2=1e-06	0.277

Hyperparameters for GCEGNN

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rateate	[0.01 to 0.00001]
Batch Size	[4, 6, 8, 12, 16]
embedding_size Size	[32, 40, 50, 60, 64]
L2 Penality	[0.0001 to 0.00001]
Epoch	[10, 12, 15]
Dropout	[0.1 to 0.5]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.207
• Standard deviation: 0.054
• Maximum value: 0.301
• Minimum value: 0.112

Parameters/Metrics	MRR@20
GCEGNN-epoch=12-lr=0.001-batch_size=16-embedding_size_size=32-dropout=0.3-l2=0.0001	0.257
GCEGNN-epoch=12-lr=0.003-batch_size=8-embedding_size_size=64-dropout=0.3-l2=0.0001	0.165
GCEGNN-epoch=12-lr=0.009-batch_size=16-embedding_size_size=64-dropout=0.1-l2=1e-05	0.255
GCEGNN-epoch=12-lr=0.0005-batch_size=12-embedding_size_size=32-dropout=0.5-l2=0.0001	0.258
GCEGNN-epoch=12-lr=0.007-batch_size=8-embedding_size_size=32-dropout=0.1-l2=1e-05	0.205
GCEGNN-epoch=12-lr=0.0004-batch_size=12-embedding_size_size=64-dropout=0.5-l2=0.0001	0.301
GCEGNN-epoch=12-lr=0.005-batch_size=8-embedding_size_size=50-dropout=0.2-l2=0.0001	0.112
GCEGNN-epoch=12-lr=0.006-batch_size=12-embedding_size_size=32-dropout=0.5-l2=1e-05	0.245
GCEGNN-epoch=12-lr=0.0003-batch_size=12-embedding_size_size=32-dropout=0.5-l2=0.0001	0.241
GCEGNN-epoch=12-lr=0.01-batch_size=8-embedding_size_size=64-dropout=0.2-l2=1e-05	0.211
GCEGNN-epoch=10-lr=0.0008-batch_size=8-embedding_size_size=40-dropout=0.2-l2=1e-05	0.270
GCEGNN-epoch=10-lr=0.01-batch_size=8-embedding_size_size=50-dropout=0.3-l2=1e-05	0.164
GCEGNN-epoch=10-lr=0.0002-batch_size=8-embedding_size_size=32-dropout=0.3-l2=1e-05	0.246
GCEGNN-epoch=10-lr=0.0007-batch_size=4-embedding_size_size=40-dropout=0.2-l2=0.0001	0.189
GCEGNN-epoch=10-lr=0.008-batch_size=4-embedding_size_size=40-dropout=0.6-l2=1e-05	0.138
GCEGNN-epoch=10-lr=0.008-batch_size=8-embedding_size_size=50-dropout=0.1-l2=1e-06	0.247
GCEGNN-epoch=10-lr=0.01-batch_size=4-embedding_size_size=32-dropout=0.5-l2=0.0001	0.124
GCEGNN-epoch=10-lr=0.001-batch_size=4-embedding_size_size=50-dropout=0.5-l2=0.0001	0.223
GCEGNN-epoch=10-lr=0.009-batch_size=4-embedding_size_size=40-dropout=0.5-l2=1e-05	0.145
GCEGNN-epoch=10-lr=0.001-batch_size=8-embedding_size_size=50-dropout=0.5-l2=1e-05	0.283
GCEGNN-epoch=10-lr=0.001-batch_size=6-embedding_size_size=50-dropout=0.6-l2=0.0003	0.210
GCEGNN-epoch=15-lr=0.007-batch_size=8-embedding_size_size=50-dropout=0.2-l2=0.0001	0.136
GCEGNN-epoch=10-lr=0.0009-batch_size=4-embedding_size_size=32-dropout=0.5-l2=0.0003	0.162
GCEGNN-epoch=10-lr=0.003-batch_size=4-embedding_size_size=50-dropout=0.3-l2=0.0001	0.171

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.242
• Standard deviation: 0.021
• Maximum value: 0.280
• Minimum value: 0.191

Parameters/Metrics	MRR@20
GCEGNN-epoch=10-lr=1e-04-batch_size=4-embedding_size_size=50-dropout=0.6-l2=1e-06	0.267
GCEGNN-epoch=10-lr=0.0004-batch_size=8-embedding_size_size=50-dropout=0.6-l2=0.0001	0.266
GCEGNN-epoch=10-lr=0.0007-batch_size=8-embedding_size_size=50-dropout=0.6-l2=1e-05	0.259
GCEGNN-epoch=10-lr=0.0005-batch_size=4-embedding_size_size=32-dropout=0.1-l2=1e-06	0.219
GCEGNN-epoch=10-lr=0.0004-batch_size=4-embedding_size_size=50-dropout=0.2-l2=1e-05	0.241
GCEGNN-epoch=10-lr=0.005-batch_size=8-embedding_size_size=50-dropout=0.2-l2=0.0001	0.213
GCEGNN-epoch=10-lr=0.007-batch_size=8-embedding_size_size=50-dropout=0.3-l2=1e-06	0.265
GCEGNN-epoch=10-lr=0.0003-batch_size=8-embedding_size_size=32-dropout=0.3-l2=0.0001	0.280
GCEGNN-epoch=10-lr=0.0008-batch_size=8-embedding_size_size=32-dropout=0.1-l2=1e-06	0.240
GCEGNN-epoch=10-lr=1e-04-batch_size=8-embedding_size_size=50-dropout=0.1-l2=1e-06	0.265
GCEGNN-epoch=10-lr=0.0007-batch_size=8-embedding_size_size=40-dropout=0.3-l2=1e-06	0.258
GCEGNN-epoch=10-lr=0.002-batch_size=8-embedding_size_size=50-dropout=0.5-l2=0.0001	0.236
GCEGNN-epoch=10-lr=0.009-batch_size=4-embedding_size_size=32-dropout=0.3-l2=1e-06	0.233
GCEGNN-epoch=10-lr=0.0007-batch_size=8-embedding_size_size=32-dropout=0.6-l2=1e-05	0.248
GCEGNN-epoch=10-lr=0.004-batch_size=8-embedding_size_size=40-dropout=0.5-l2=0.0001	0.217
GCEGNN-epoch=10-lr=0.009-batch_size=6-embedding_size_size=32-dropout=0.5-l2=1e-06	0.236
GCEGNN-epoch=10-lr=0.008-batch_size=6-embedding_size_size=40-dropout=0.2-l2=1e-05	0.212
GCEGNN-epoch=10-lr=0.008-batch_size=6-embedding_size_size=40-dropout=0.1-l2=1e-06	0.249
GCEGNN-epoch=10-lr=0.008-batch_size=4-embedding_size_size=32-dropout=0.3-l2=1e-05	0.191
GCEGNN-epoch=10-lr=0.006-batch_size=6-embedding_size_size=32-dropout=0.2-l2=1e-06	0.236
GCEGNN-epoch=15-lr=1e-04-batch_size=4-embedding_size_size=32-dropout=0.1-l2=0.0003	0.252
GCEGNN-epoch=10-lr=0.0005-batch_size=4-embedding_size_size=40-dropout=0.2-l2=0.0003	0.241
GCEGNN-epoch=10-lr=0.0008-batch_size=8-embedding_size_size=32-dropout=0.2-l2=1e-06	0.247
GCEGNN-epoch=15-lr=0.006-batch_size=4-embedding_size_size=32-dropout=0.2-l2=1e-06	0.218
GCEGNN-epoch=10-lr=0.0002-batch_size=6-embedding_size_size=40-dropout=0.6-l2=0.0003	0.271
GCEGNN-epoch=15-lr=0.004-batch_size=8-embedding_size_size=40-dropout=0.2-l2=1e-05	0.247
GCEGNN-epoch=10-lr=0.01-batch_size=4-embedding_size_size=40-dropout=0.5-l2=1e-06	0.228

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.239
• Standard deviation: 0.073
• Maximum value: 0.341
• Minimum value: 0.087

Parameters/Metrics	MRR@20
GCEGNN-epoch=12-lr=0.001-batch_size=4-embedding_size=40-dropout=0.3-l2=1e-05	0.294
GCEGNN-epoch=12-lr=0.004-batch_size=4-embedding_size=40-dropout=0.6-l2=0.0001	0.191
GCEGNN-epoch=12-lr=0.0005-batch_size=8-embedding_size=60-dropout=0.5-l2=0.0001	0.341
GCEGNN-epoch=12-lr=0.005-batch_size=4-embedding_size=80-dropout=0.2-l2=1e-05	0.237
GCEGNN-epoch=12-lr=0.008-batch_size=6-embedding_size=40-dropout=0.1-l2=0.0001	0.151
GCEGNN-epoch=12-lr=0.0009-batch_size=8-embedding_size=60-dropout=0.3-l2=0.0001	0.297
GCEGNN-epoch=12-lr=0.003-batch_size=6-embedding_size=60-dropout=0.5-l2=1e-05	0.235
GCEGNN-epoch=12-lr=0.003-batch_size=8-embedding_size=60-dropout=0.2-l2=0.0001	0.224
GCEGNN-epoch=12-lr=0.0002-batch_size=8-embedding_size=40-dropout=0.2-l2=1e-05	0.309
GCEGNN-epoch=12-lr=0.005-batch_size=4-embedding_size=40-dropout=0.7-l2=1e-05	0.142
GCEGNN-epoch=10-lr=0.005-batch_size=6-embedding_size=32-dropout=0.5-l2=1e-06	0.211
GCEGNN-epoch=15-lr=0.008-batch_size=8-embedding_size=50-dropout=0.1-l2=1e-05	0.251
GCEGNN-epoch=12-lr=0.004-batch_size=4-embedding_size=40-dropout=0.5-l2=0.0003	0.131
GCEGNN-epoch=10-lr=0.0009-batch_size=8-embedding_size=50-dropout=0.5-l2=0.0003	0.323
GCEGNN-epoch=15-lr=0.005-batch_size=6-embedding_size=32-dropout=0.1-l2=0.0001	0.146
GCEGNN-epoch=10-lr=0.009-batch_size=8-embedding_size=32-dropout=0.2-l2=0.0003	0.087
GCEGNN-epoch=12-lr=0.0002-batch_size=4-embedding_size=50-dropout=0.6-l2=1e-06	0.306
GCEGNN-epoch=12-lr=0.0003-batch_size=8-embedding_size=50-dropout=0.2-l2=0.0001	0.336
GCEGNN-epoch=12-lr=0.0006-batch_size=8-embedding_size=32-dropout=0.6-l2=1e-06	0.330
GCEGNN-epoch=10-lr=0.008-batch_size=8-embedding_size=50-dropout=0.2-l2=1e-06	0.302
GCEGNN-epoch=12-lr=0.003-batch_size=4-embedding_size=32-dropout=0.6-l2=1e-05	0.213
GCEGNN-epoch=15-lr=0.0005-batch_size=8-embedding_size=40-dropout=0.5-l2=0.0003	0.281
GCEGNN-epoch=12-lr=0.007-batch_size=8-embedding_size=40-dropout=0.1-l2=1e-06	0.285
GCEGNN-epoch=10-lr=0.004-batch_size=6-embedding_size=40-dropout=0.2-l2=1e-06	0.269
GCEGNN-epoch=10-lr=0.01-batch_size=8-embedding_size=40-dropout=0.5-l2=0.0001	0.154
GCEGNN-epoch=10-lr=0.0008-batch_size=8-embedding_size=40-dropout=0.5-l2=1e-06	0.335
GCEGNN-epoch=10-lr=0.01-batch_size=4-embedding_size=32-dropout=0.2-l2=1e-05	0.186
GCEGNN-epoch=10-lr=0.007-batch_size=6-embedding_size=40-dropout=0.3-l2=1e-05	0.194
GCEGNN-epoch=10-lr=1e-04-batch_size=4-embedding_size=32-dropout=0.5-l2=1e-05	0.183

Hyperparameters for SR-GNN

We tested the following hyperparameter space:

Parameter	Ranges
Learning Rateate	[0.01 to 0.00001]
Batch Size	[100, 128, 200, 256]
embedding_size Size	[50, 100, 150, 200]
L2 Penality	[0.0001 to 0.00001]
Epoch	[10, 15, 20]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.324
• Standard deviation: 0.024
• Maximum value: 0.360
• Minimum value: 0.282

Parameters/Metrics	MRR@20
GGNN-epoch=10-lr=0.0009-embedding_size=50-batch_size=200-l2=1e-05	0.335
GGNN-epoch=10-lr=0.0008-embedding_size=150-batch_size=256-l2=0.0003	0.317
GGNN-epoch=10-lr=0.0008-embedding_size=150-batch_size=200-l2=1e-05	0.293
GGNN-epoch=10-lr=0.0004-embedding_size=50-batch_size=256-l2=0.0003	0.339
GGNN-epoch=10-lr=0.0005-embedding_size=100-batch_size=128-l2=0.0001	0.328
GGNN-epoch=10-lr=0.0007-embedding_size=200-batch_size=100-l2=0.0003	0.303
GGNN-epoch=10-lr=0.0009-embedding_size=50-batch_size=200-l2=0.0001	0.345
GGNN-epoch=10-lr=0.005-embedding_size=150-batch_size=128-l2=1e-05	0.335
GGNN-epoch=10-lr=0.001-embedding_size=200-batch_size=128-l2=1e-05	0.285
GGNN-epoch=10-lr=0.0003-embedding_size=100-batch_size=200-l2=1e-05	0.311
GGNN-epoch=10-lr=0.007-embedding_size=100-batch_size=200-l2=0.0003	0.342
GGNN-epoch=15-lr=0.01-embedding_size=50-batch_size=100-l2=0.0003	0.330
GGNN-epoch=10-lr=0.0004-embedding_size=200-batch_size=128-l2=0.0003	0.329
GGNN-epoch=20-lr=0.006-embedding_size=100-batch_size=256-l2=0.0003	0.354
GGNN-epoch=15-lr=0.0008-embedding_size=50-batch_size=256-l2=0.0001	0.347
GGNN-epoch=20-lr=0.008-embedding_size=150-batch_size=200-l2=0.0001	0.344
GGNN-epoch=10-lr=0.001-embedding_size=50-batch_size=100-l2=1e-05	0.332
GGNN-epoch=10-lr=0.0002-embedding_size=200-batch_size=150-l2=1e-05	0.283
GGNN-epoch=20-lr=0.01-embedding_size=150-batch_size=150-l2=0.0003	0.338
GGNN-epoch=10-lr=0.006-embedding_size=100-batch_size=128-l2=0.0003	0.360
GGNN-epoch=10-lr=0.005-embedding_size=150-batch_size=150-l2=0.0001	0.311
GGNN-epoch=20-lr=0.0006-embedding_size=50-batch_size=200-l2=0.0001	0.358
GGNN-epoch=15-lr=0.001-embedding_size=200-batch_size=200-l2=0.0001	0.282
GGNN-epoch=15-lr=0.001-embedding_size=200-batch_size=100-l2=0.0003	0.307
GGNN-epoch=15-lr=0.0007-embedding_size=200-batch_size=200-l2=1e-05	0.284

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.255
• Standard deviation: 0.012
• Maximum value: 0.270
• Minimum value: 0.226

Parameters/Metrics	MRR@20
GGNN-epoch=10-lr=0.0003-embedding_size=100-batch_size=150-l2=0.0003	0.233
GGNN-epoch=10-lr=0.0004-embedding_size=50-batch_size=128-l2=0.0001	0.226
GGNN-epoch=10-lr=0.009-embedding_size=50-batch_size=200-l2=0.0001	0.270
GGNN-epoch=10-lr=0.004-embedding_size=150-batch_size=128-l2=0.0001	0.269
GGNN-epoch=10-lr=0.006-embedding_size=50-batch_size=100-l2=0.0001	0.268
GGNN-epoch=10-lr=0.005-embedding_size=150-batch_size=200-l2=0.0001	0.263
GGNN-epoch=10-lr=0.002-embedding_size=100-batch_size=200-l2=0.0003	0.257
GGNN-epoch=10-lr=0.0006-embedding_size=100-batch_size=256-l2=0.0003	0.253
GGNN-epoch=10-lr=0.0007-embedding_size=200-batch_size=256-l2=0.0003	0.246
GGNN-epoch=10-lr=0.002-embedding_size=150-batch_size=150-l2=0.0001	0.262
GGNN-epoch=15-lr=0.008-embedding_size=200-batch_size=256-l2=1e-05	0.258
GGNN-epoch=10-lr=0.005-embedding_size=50-batch_size=128-l2=1e-05	0.266
GGNN-epoch=15-lr=1e-04-embedding_size=150-batch_size=150-l2=0.0001	0.233
GGNN-epoch=20-lr=0.002-embedding_size=200-batch_size=150-l2=0.0003	0.264
GGNN-epoch=20-lr=0.008-embedding_size=200-batch_size=200-l2=0.0001	0.249
GGNN-epoch=15-lr=0.001-embedding_size=100-batch_size=100-l2=0.0001	0.269
GGNN-epoch=10-lr=0.006-embedding_size=150-batch_size=100-l2=0.0001	0.258
GGNN-epoch=20-lr=0.0006-embedding_size=150-batch_size=100-l2=0.0003	0.252
GGNN-epoch=10-lr=0.0002-embedding_size=150-batch_size=100-l2=0.0003	0.236
GGNN-epoch=15-lr=0.0007-embedding_size=50-batch_size=256-l2=0.0001	0.247
GGNN-epoch=15-lr=0.001-embedding_size=150-batch_size=150-l2=0.0003	0.255
GGNN-epoch=15-lr=0.0006-embedding_size=100-batch_size=100-l2=0.0001	0.263
GGNN-epoch=20-lr=0.001-embedding_size=200-batch_size=200-l2=1e-05	0.262
GGNN-epoch=10-lr=0.0009-embedding_size=100-batch_size=200-l2=1e-05	0.262
GGNN-epoch=10-lr=0.0009-embedding_size=50-batch_size=100-l2=0.0001	0.253
GGNN-epoch=20-lr=0.005-embedding_size=50-batch_size=200-l2=0.0003	0.263

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.586
• Standard deviation: 0.019
• Maximum value: 0.621
• Minimum value: 0.529

Parameters/Metrics	MRR@20
GGNN-epoch=10-lr=0.0005-embedding_size=200-batch_size=200-l2=0.0001	0.589
GGNN-epoch=10-lr=0.004-embedding_size=150-batch_size=256-l2=1e-05	0.621
GGNN-epoch=10-lr=0.0009-embedding_size=100-batch_size=128-l2=1e-05	0.603
GGNN-epoch=10-lr=0.005-embedding_size=50-batch_size=150-l2=0.0001	0.584
GGNN-epoch=10-lr=0.009-embedding_size=150-batch_size=128-l2=1e-05	0.583
GGNN-epoch=10-lr=0.002-embedding_size=200-batch_size=200-l2=0.0001	0.610
GGNN-epoch=10-lr=0.0008-embedding_size=50-batch_size=128-l2=1e-05	0.575
GGNN-epoch=10-lr=0.009-embedding_size=150-batch_size=200-l2=0.0003	0.590
GGNN-epoch=10-lr=0.0002-embedding_size=50-batch_size=200-l2=0.0003	0.529
GGNN-epoch=10-lr=0.0004-embedding_size=200-batch_size=100-l2=0.0001	0.588
GGNN-epoch=15-lr=0.0004-embedding_size=50-batch_size=100-l2=0.0003	0.575
GGNN-epoch=20-lr=0.005-embedding_size=50-batch_size=150-l2=1e-05	0.598
GGNN-epoch=20-lr=0.009-embedding_size=200-batch_size=128-l2=0.0001	0.614
GGNN-epoch=20-lr=0.002-embedding_size=100-batch_size=128-l2=0.0003	0.576
GGNN-epoch=15-lr=0.001-embedding_size=200-batch_size=128-l2=0.0003	0.588
GGNN-epoch=10-lr=0.0005-embedding_size=50-batch_size=200-l2=0.0003	0.572
GGNN-epoch=20-lr=0.01-embedding_size=200-batch_size=128-l2=0.0003	0.583
GGNN-epoch=10-lr=0.005-embedding_size=100-batch_size=100-l2=0.0001	0.612
GGNN-epoch=10-lr=0.002-embedding_size=50-batch_size=150-l2=1e-05	0.584
GGNN-epoch=15-lr=0.002-embedding_size=100-batch_size=256-l2=0.0003	0.583
GGNN-epoch=20-lr=0.0004-embedding_size=150-batch_size=200-l2=0.0001	0.577
GGNN-epoch=20-lr=0.0003-embedding_size=200-batch_size=150-l2=1e-05	0.582
GGNN-epoch=20-lr=0.0003-embedding_size=200-batch_size=200-l2=1e-05	0.579
GGNN-epoch=10-lr=0.005-embedding_size=50-batch_size=100-l2=1e-05	0.598
GGNN-epoch=20-lr=0.0002-embedding_size=50-batch_size=100-l2=0.0001	0.557

Hyperparameters for STAN

We tested the following hyperparameter space:

Parameter	Options
Number of Neighbors	[50, 100, 500, 600, 700, 800, 1000, 1300, 1400, 1500, 1700, 2000, 2500, 2800, 3000]
Sample Size	[500, 600, 1000, 1100, 2500, 1900, 5000, 7000, 8000, 10000]
lambda_spw	[0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, 0.99, 0.11, 0.12, 0.101, 0.102, 0.103, 0.104, 0.105, 0.106, 0.107, 0.108, 0.15, 0.16, 1.2, 1.8, 2.4]
lambda_snh	[50, 57, 80, 100, 150, 200, 400, 450, 470, 500, 520, 530, 600]
lambda_inh	[0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 1.8, 2, 2.5, 2.8, 3, 3.5, 3.8, 4]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.379
• Standard deviation: 0.005
• Maximum value: 0.386
• Minimum value: 0.364

Parameter/Metrics	MRR@20
stan-k=570-sample_size=2700-lambda_spw=0.81-lambda_snh=600-lambda_inh=5	0.369
stan-k=510-sample_size=2900-lambda_spw=0.15-lambda_snh=10-lambda_inh=0.55	0.382
stan-k=4000-sample_size=2900-lambda_spw=0.13-lambda_snh=150-lambda_inh=0.57	0.383
stan-k=4500-sample_size=2000-lambda_spw=0.13-lambda_snh=450-lambda_inh=2	0.383
stan-k=600-sample_size=2700-lambda_spw=0.13-lambda_snh=150-lambda_inh=0.5	0.382
stan-k=4500-sample_size=2650-lambda_spw=0.15-lambda_snh=50-lambda_inh=0.58	0.385
stan-k=4000-sample_size=1000-lambda_spw=0.4-lambda_snh=500-lambda_inh=0.55	0.376
stan-k=3500-sample_size=2800-lambda_spw=0.7-lambda_snh=600-lambda_inh=2	0.374
stan-k=5500-sample_size=2650-lambda_spw=0.4-lambda_snh=470-lambda_inh=0.58	0.376
stan-k=2500-sample_size=2000-lambda_spw=0.4-lambda_snh=400-lambda_inh=0.57	0.376
stan-k=600-sample_size=2800-lambda_spw=0.81-lambda_snh=400-lambda_inh=5	0.369
stan-k=5500-sample_size=500-lambda_spw=0.7-lambda_snh=530-lambda_inh=5	0.373
stan-k=600-sample_size=2500-lambda_spw=0.81-lambda_snh=350-lambda_inh=6	0.369
stan-k=3000-sample_size=1000-lambda_spw=0.81-lambda_snh=530-lambda_inh=0.55	0.365
stan-k=3000-sample_size=2500-lambda_spw=0.16-lambda_snh=25-lambda_inh=0.5	0.386
stan-k=750-sample_size=2000-lambda_spw=0.14-lambda_snh=300-lambda_inh=1.5	0.384
stan-k=530-sample_size=2500-lambda_spw=0.12-lambda_snh=100-lambda_inh=0.58	0.383
stan-k=570-sample_size=500-lambda_spw=0.4-lambda_snh=350-lambda_inh=0.55	0.376
stan-k=4500-sample_size=2900-lambda_spw=0.16-lambda_snh=50-lambda_inh=1.5	0.386
stan-k=4000-sample_size=2700-lambda_spw=0.35-lambda_snh=530-lambda_inh=0.51	0.376
stan-k=750-sample_size=2500-lambda_spw=0.6-lambda_snh=50-lambda_inh=0.54	0.374
stan-k=700-sample_size=2800-lambda_spw=0.4-lambda_snh=470-lambda_inh=0.53	0.375
stan-k=600-sample_size=2000-lambda_spw=0.12-lambda_snh=50-lambda_inh=0.51	0.384
stan-k=4500-sample_size=2000-lambda_spw=0.12-lambda_snh=10-lambda_inh=2	0.386
stan-k=1500-sample_size=2000-lambda_spw=0.12-lambda_snh=100-lambda_inh=0.52	0.383
stan-k=510-sample_size=2800-lambda_spw=0.81-lambda_snh=150-lambda_inh=0.57	0.365
stan-k=2800-sample_size=2700-lambda_spw=0.81-lambda_snh=350-lambda_inh=0.56	0.364
stan-k=3500-sample_size=2000-lambda_spw=0.7-lambda_snh=250-lambda_inh=1.5	0.375
stan-k=2000-sample_size=2800-lambda_spw=0.81-lambda_snh=500-lambda_inh=0.5	0.364
stan-k=5000-sample_size=2700-lambda_spw=0.6-lambda_snh=350-lambda_inh=0.5	0.370
stan-k=2000-sample_size=2800-lambda_spw=0.4-lambda_snh=150-lambda_inh=0.52	0.376
stan-k=4000-sample_size=2550-lambda_spw=0.35-lambda_snh=450-lambda_inh=0.51	0.376
stan-k=5000-sample_size=2900-lambda_spw=0.7-lambda_snh=50-lambda_inh=1	0.374
stan-k=750-sample_size=2500-lambda_spw=0.14-lambda_snh=470-lambda_inh=1.5	0.383
stan-k=750-sample_size=500-lambda_spw=0.13-lambda_snh=450-lambda_inh=6	0.382
stan-k=1500-sample_size=2550-lambda_spw=0.1-lambda_snh=250-lambda_inh=7	0.382
stan-k=5500-sample_size=2000-lambda_spw=0.16-lambda_snh=530-lambda_inh=0.55	0.382
stan-k=1500-sample_size=2700-lambda_spw=0.7-lambda_snh=600-lambda_inh=7	0.374
stan-k=530-sample_size=500-lambda_spw=0.6-lambda_snh=300-lambda_inh=0.55	0.372
stan-k=600-sample_size=3000-lambda_spw=0.1-lambda_snh=300-lambda_inh=20	0.379
stan-k=1500-sample_size=1500-lambda_spw=0.1-lambda_snh=50-lambda_inh=0.54	0.384
stan-k=3500-sample_size=1000-lambda_spw=0.17-lambda_snh=530-lambda_inh=0.54	0.382
stan-k=600-sample_size=2550-lambda_spw=0.15-lambda_snh=450-lambda_inh=0.53	0.383
stan-k=6000-sample_size=2500-lambda_spw=0.12-lambda_snh=600-lambda_inh=1.5	0.383
stan-k=2500-sample_size=2650-lambda_spw=0.1-lambda_snh=520-lambda_inh=0.51	0.383
stan-k=5500-sample_size=2550-lambda_spw=0.15-lambda_snh=50-lambda_inh=0.53	0.384
stan-k=700-sample_size=2500-lambda_spw=0.13-lambda_snh=100-lambda_inh=9	0.381
stan-k=750-sample_size=3000-lambda_spw=0.35-lambda_snh=150-lambda_inh=9	0.379
stan-k=3500-sample_size=2500-lambda_spw=0.81-lambda_snh=450-lambda_inh=7	0.368
stan-k=4000-sample_size=2650-lambda_spw=0.1-lambda_snh=100-lambda_inh=0.5	0.383
stan-k=700-sample_size=2550-lambda_spw=0.14-lambda_snh=520-lambda_inh=0.55	0.383
stan-k=4000-sample_size=2800-lambda_spw=0.12-lambda_snh=100-lambda_inh=6	0.382
stan-k=2800-sample_size=1000-lambda_spw=0.15-lambda_snh=50-lambda_inh=0.5	0.383
stan-k=4500-sample_size=1000-lambda_spw=0.1-lambda_snh=250-lambda_inh=2	0.383
stan-k=1500-sample_size=2800-lambda_spw=0.81-lambda_snh=50-lambda_inh=20	0.370
stan-k=2500-sample_size=2000-lambda_spw=0.15-lambda_snh=500-lambda_inh=1	0.382
stan-k=4500-sample_size=2550-lambda_spw=0.14-lambda_snh=470-lambda_inh=7	0.382
stan-k=570-sample_size=2500-lambda_spw=0.4-lambda_snh=150-lambda_inh=0.56	0.376
stan-k=2000-sample_size=500-lambda_spw=0.15-lambda_snh=300-lambda_inh=0.52	0.383
stan-k=2000-sample_size=2550-lambda_spw=0.15-lambda_snh=200-lambda_inh=6	0.383
stan-k=2000-sample_size=2550-lambda_spw=0.12-lambda_snh=200-lambda_inh=0.56	0.383
stan-k=530-sample_size=2650-lambda_spw=0.6-lambda_snh=10-lambda_inh=0.52	0.372
stan-k=4000-sample_size=2000-lambda_spw=0.35-lambda_snh=100-lambda_inh=0.55	0.378
stan-k=3000-sample_size=1500-lambda_spw=0.16-lambda_snh=50-lambda_inh=1	0.386
stan-k=5500-sample_size=1000-lambda_spw=0.17-lambda_snh=300-lambda_inh=20	0.379
stan-k=700-sample_size=2700-lambda_spw=0.35-lambda_snh=25-lambda_inh=9	0.380
stan-k=1500-sample_size=1000-lambda_spw=0.81-lambda_snh=100-lambda_inh=0.57	0.366
stan-k=3000-sample_size=1000-lambda_spw=0.1-lambda_snh=450-lambda_inh=0.55	0.383
stan-k=4500-sample_size=500-lambda_spw=0.35-lambda_snh=450-lambda_inh=7	0.380
stan-k=510-sample_size=1000-lambda_spw=0.4-lambda_snh=200-lambda_inh=0.56	0.377
stan-k=630-sample_size=3000-lambda_spw=0.13-lambda_snh=200-lambda_inh=0.57	0.383
stan-k=5500-sample_size=2650-lambda_spw=0.17-lambda_snh=350-lambda_inh=1.5	0.383
stan-k=5500-sample_size=2900-lambda_spw=0.4-lambda_snh=200-lambda_inh=0.58	0.377
stan-k=700-sample_size=500-lambda_spw=0.13-lambda_snh=200-lambda_inh=20	0.379
stan-k=600-sample_size=2550-lambda_spw=0.4-lambda_snh=10-lambda_inh=0.57	0.377
stan-k=570-sample_size=1500-lambda_spw=0.4-lambda_snh=400-lambda_inh=15	0.378
stan-k=5500-sample_size=2550-lambda_spw=0.35-lambda_snh=25-lambda_inh=0.53	0.381
stan-k=700-sample_size=1000-lambda_spw=0.35-lambda_snh=350-lambda_inh=0.55	0.377
stan-k=2500-sample_size=500-lambda_spw=0.7-lambda_snh=25-lambda_inh=0.54	0.373
stan-k=600-sample_size=2000-lambda_spw=0.4-lambda_snh=470-lambda_inh=0.53	0.376
stan-k=3500-sample_size=2700-lambda_spw=0.7-lambda_snh=250-lambda_inh=1	0.373
stan-k=630-sample_size=2000-lambda_spw=0.13-lambda_snh=25-lambda_inh=6	0.385
stan-k=6000-sample_size=1000-lambda_spw=0.17-lambda_snh=400-lambda_inh=1.5	0.383
stan-k=750-sample_size=2000-lambda_spw=0.35-lambda_snh=150-lambda_inh=1.5	0.380
stan-k=1500-sample_size=500-lambda_spw=0.4-lambda_snh=250-lambda_inh=1	0.378
stan-k=3000-sample_size=1500-lambda_spw=0.13-lambda_snh=100-lambda_inh=0.52	0.383
stan-k=5000-sample_size=2000-lambda_spw=0.16-lambda_snh=530-lambda_inh=20	0.379
stan-k=570-sample_size=1000-lambda_spw=0.17-lambda_snh=470-lambda_inh=0.55	0.382
stan-k=4000-sample_size=500-lambda_spw=0.17-lambda_snh=25-lambda_inh=20	0.382
stan-k=2800-sample_size=1000-lambda_spw=0.1-lambda_snh=470-lambda_inh=2	0.383
stan-k=700-sample_size=1000-lambda_spw=0.16-lambda_snh=50-lambda_inh=15	0.381
stan-k=530-sample_size=2900-lambda_spw=0.17-lambda_snh=600-lambda_inh=2	0.383
stan-k=510-sample_size=500-lambda_spw=0.4-lambda_snh=150-lambda_inh=9	0.379
stan-k=2000-sample_size=2650-lambda_spw=0.1-lambda_snh=50-lambda_inh=0.5	0.384
stan-k=630-sample_size=3000-lambda_spw=0.4-lambda_snh=100-lambda_inh=0.55	0.377
stan-k=4500-sample_size=1500-lambda_spw=0.7-lambda_snh=520-lambda_inh=15	0.372
stan-k=750-sample_size=1000-lambda_spw=0.81-lambda_snh=25-lambda_inh=1	0.373
stan-k=3500-sample_size=2800-lambda_spw=0.12-lambda_snh=150-lambda_inh=20	0.379
stan-k=570-sample_size=500-lambda_spw=0.81-lambda_snh=25-lambda_inh=1	0.373
stan-k=630-sample_size=1000-lambda_spw=0.14-lambda_snh=520-lambda_inh=2	0.383

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.285
• Standard deviation: 0.002
• Maximum value: 0.289
• Minimum value: 0.279

Parameter/Metrics	MRR@20
stan-k=4000-sample_size=1500-lambda_spw=0.14-lambda_snh=100-lambda_inh=0.54	0.285
stan-k=1500-sample_size=2650-lambda_spw=0.17-lambda_snh=470-lambda_inh=0.5	0.285
stan-k=700-sample_size=2900-lambda_spw=0.81-lambda_snh=300-lambda_inh=1.5	0.288
stan-k=700-sample_size=3000-lambda_spw=0.12-lambda_snh=50-lambda_inh=0.52	0.284
stan-k=2000-sample_size=2800-lambda_spw=0.17-lambda_snh=50-lambda_inh=1.5	0.285
stan-k=5000-sample_size=1500-lambda_spw=0.14-lambda_snh=100-lambda_inh=0.56	0.285
stan-k=530-sample_size=500-lambda_spw=0.12-lambda_snh=200-lambda_inh=0.5	0.284
stan-k=2000-sample_size=2800-lambda_spw=0.13-lambda_snh=350-lambda_inh=0.58	0.285
stan-k=570-sample_size=2700-lambda_spw=0.81-lambda_snh=25-lambda_inh=0.56	0.282
stan-k=5500-sample_size=2800-lambda_spw=0.1-lambda_snh=200-lambda_inh=6	0.284
stan-k=570-sample_size=1000-lambda_spw=0.16-lambda_snh=300-lambda_inh=0.54	0.285
stan-k=700-sample_size=1000-lambda_spw=0.16-lambda_snh=530-lambda_inh=1.5	0.285
stan-k=2800-sample_size=2900-lambda_spw=0.7-lambda_snh=400-lambda_inh=15	0.286
stan-k=700-sample_size=2800-lambda_spw=0.16-lambda_snh=450-lambda_inh=2	0.285
stan-k=570-sample_size=2500-lambda_spw=0.1-lambda_snh=470-lambda_inh=20	0.284
stan-k=5500-sample_size=2650-lambda_spw=0.81-lambda_snh=600-lambda_inh=6	0.287
stan-k=2500-sample_size=2500-lambda_spw=0.1-lambda_snh=100-lambda_inh=2	0.285
stan-k=750-sample_size=2700-lambda_spw=0.12-lambda_snh=150-lambda_inh=0.57	0.285
stan-k=700-sample_size=2550-lambda_spw=0.13-lambda_snh=250-lambda_inh=1	0.285
stan-k=3000-sample_size=2000-lambda_spw=0.13-lambda_snh=450-lambda_inh=9	0.284
stan-k=5500-sample_size=2000-lambda_spw=0.81-lambda_snh=600-lambda_inh=5	0.288
stan-k=4500-sample_size=2550-lambda_spw=0.17-lambda_snh=50-lambda_inh=9	0.284
stan-k=530-sample_size=500-lambda_spw=0.14-lambda_snh=300-lambda_inh=0.55	0.285
stan-k=2800-sample_size=2650-lambda_spw=0.16-lambda_snh=530-lambda_inh=2	0.286
stan-k=750-sample_size=3000-lambda_spw=0.15-lambda_snh=250-lambda_inh=0.53	0.285
stan-k=2000-sample_size=2900-lambda_spw=0.15-lambda_snh=25-lambda_inh=15	0.284
stan-k=530-sample_size=1500-lambda_spw=0.12-lambda_snh=350-lambda_inh=2	0.286
stan-k=2800-sample_size=3000-lambda_spw=0.16-lambda_snh=400-lambda_inh=7	0.284
stan-k=630-sample_size=2650-lambda_spw=0.16-lambda_snh=200-lambda_inh=0.57	0.285
stan-k=2000-sample_size=2550-lambda_spw=0.6-lambda_snh=150-lambda_inh=5	0.288
stan-k=3000-sample_size=1500-lambda_spw=0.6-lambda_snh=500-lambda_inh=0.57	0.281
stan-k=630-sample_size=2500-lambda_spw=0.7-lambda_snh=450-lambda_inh=0.5	0.279
stan-k=5000-sample_size=2700-lambda_spw=0.81-lambda_snh=300-lambda_inh=0.56	0.282
stan-k=5000-sample_size=2800-lambda_spw=0.6-lambda_snh=530-lambda_inh=0.53	0.282
stan-k=4500-sample_size=2900-lambda_spw=0.12-lambda_snh=520-lambda_inh=0.51	0.284
stan-k=700-sample_size=3000-lambda_spw=0.15-lambda_snh=450-lambda_inh=15	0.284
stan-k=5500-sample_size=500-lambda_spw=0.13-lambda_snh=200-lambda_inh=9	0.285
stan-k=570-sample_size=1500-lambda_spw=0.81-lambda_snh=350-lambda_inh=20	0.287
stan-k=600-sample_size=2000-lambda_spw=0.6-lambda_snh=25-lambda_inh=6	0.287
stan-k=6000-sample_size=2550-lambda_spw=0.16-lambda_snh=400-lambda_inh=0.53	0.285
stan-k=5000-sample_size=1000-lambda_spw=0.1-lambda_snh=500-lambda_inh=7	0.284
stan-k=4000-sample_size=2500-lambda_spw=0.17-lambda_snh=250-lambda_inh=1.5	0.286
stan-k=700-sample_size=2700-lambda_spw=0.6-lambda_snh=500-lambda_inh=1.5	0.289
stan-k=3000-sample_size=3000-lambda_spw=0.4-lambda_snh=250-lambda_inh=9	0.287
stan-k=5500-sample_size=1000-lambda_spw=0.4-lambda_snh=520-lambda_inh=0.53	0.284
stan-k=600-sample_size=2000-lambda_spw=0.81-lambda_snh=450-lambda_inh=5	0.288
stan-k=5500-sample_size=2500-lambda_spw=0.13-lambda_snh=10-lambda_inh=0.56	0.286
stan-k=2800-sample_size=2800-lambda_spw=0.6-lambda_snh=10-lambda_inh=0.56	0.283
stan-k=2500-sample_size=3000-lambda_spw=0.17-lambda_snh=500-lambda_inh=6	0.284
stan-k=750-sample_size=1000-lambda_spw=0.1-lambda_snh=530-lambda_inh=7	0.284
stan-k=1500-sample_size=1000-lambda_spw=0.14-lambda_snh=530-lambda_inh=0.54	0.284
stan-k=750-sample_size=2000-lambda_spw=0.17-lambda_snh=450-lambda_inh=0.56	0.285
stan-k=6000-sample_size=2000-lambda_spw=0.1-lambda_snh=100-lambda_inh=7	0.284
stan-k=2500-sample_size=2650-lambda_spw=0.4-lambda_snh=300-lambda_inh=0.52	0.283
stan-k=4500-sample_size=2800-lambda_spw=0.17-lambda_snh=25-lambda_inh=1	0.285
stan-k=600-sample_size=2550-lambda_spw=0.12-lambda_snh=25-lambda_inh=0.56	0.284
stan-k=3500-sample_size=2700-lambda_spw=0.13-lambda_snh=250-lambda_inh=1	0.285
stan-k=4000-sample_size=1500-lambda_spw=0.17-lambda_snh=250-lambda_inh=0.52	0.285
stan-k=2000-sample_size=2800-lambda_spw=0.4-lambda_snh=400-lambda_inh=0.52	0.283
stan-k=700-sample_size=2650-lambda_spw=0.1-lambda_snh=350-lambda_inh=0.57	0.285
stan-k=570-sample_size=2000-lambda_spw=0.17-lambda_snh=350-lambda_inh=1.5	0.286
stan-k=1500-sample_size=1000-lambda_spw=0.12-lambda_snh=350-lambda_inh=1.5	0.285
stan-k=5500-sample_size=2000-lambda_spw=0.81-lambda_snh=250-lambda_inh=1	0.286
stan-k=3000-sample_size=2650-lambda_spw=0.16-lambda_snh=150-lambda_inh=0.58	0.285
stan-k=5000-sample_size=1000-lambda_spw=0.15-lambda_snh=530-lambda_inh=0.55	0.285
stan-k=570-sample_size=2500-lambda_spw=0.16-lambda_snh=400-lambda_inh=15	0.284
stan-k=530-sample_size=2550-lambda_spw=0.17-lambda_snh=450-lambda_inh=20	0.284
stan-k=3500-sample_size=3000-lambda_spw=0.12-lambda_snh=200-lambda_inh=0.51	0.284
stan-k=5500-sample_size=500-lambda_spw=0.6-lambda_snh=100-lambda_inh=5	0.288
stan-k=700-sample_size=500-lambda_spw=0.6-lambda_snh=500-lambda_inh=15	0.286
stan-k=6000-sample_size=2900-lambda_spw=0.14-lambda_snh=470-lambda_inh=1	0.285
stan-k=750-sample_size=1000-lambda_spw=0.81-lambda_snh=470-lambda_inh=1.5	0.288
stan-k=750-sample_size=2500-lambda_spw=0.17-lambda_snh=300-lambda_inh=20	0.284
stan-k=630-sample_size=2650-lambda_spw=0.14-lambda_snh=520-lambda_inh=9	0.284
stan-k=3000-sample_size=2650-lambda_spw=0.14-lambda_snh=10-lambda_inh=6	0.284
stan-k=510-sample_size=1500-lambda_spw=0.14-lambda_snh=400-lambda_inh=9	0.284
stan-k=2800-sample_size=2700-lambda_spw=0.14-lambda_snh=530-lambda_inh=0.58	0.285
stan-k=2800-sample_size=1500-lambda_spw=0.4-lambda_snh=350-lambda_inh=0.54	0.284
stan-k=700-sample_size=3000-lambda_spw=0.6-lambda_snh=530-lambda_inh=0.54	0.281
stan-k=2000-sample_size=1500-lambda_spw=0.14-lambda_snh=530-lambda_inh=0.55	0.284
stan-k=600-sample_size=2700-lambda_spw=0.81-lambda_snh=50-lambda_inh=5	0.288
stan-k=750-sample_size=2500-lambda_spw=0.6-lambda_snh=150-lambda_inh=9	0.288
stan-k=750-sample_size=500-lambda_spw=0.6-lambda_snh=470-lambda_inh=0.58	0.282
stan-k=530-sample_size=500-lambda_spw=0.12-lambda_snh=470-lambda_inh=0.5	0.284
stan-k=510-sample_size=2900-lambda_spw=0.15-lambda_snh=150-lambda_inh=0.58	0.285
stan-k=700-sample_size=2700-lambda_spw=0.35-lambda_snh=600-lambda_inh=0.56	0.287
stan-k=570-sample_size=2550-lambda_spw=0.35-lambda_snh=450-lambda_inh=7	0.286
stan-k=6000-sample_size=500-lambda_spw=0.14-lambda_snh=530-lambda_inh=7	0.285
stan-k=700-sample_size=3000-lambda_spw=0.7-lambda_snh=300-lambda_inh=15	0.286
stan-k=530-sample_size=2650-lambda_spw=0.7-lambda_snh=300-lambda_inh=6	0.288
stan-k=600-sample_size=3000-lambda_spw=0.1-lambda_snh=600-lambda_inh=2	0.285
stan-k=2500-sample_size=1500-lambda_spw=0.7-lambda_snh=300-lambda_inh=0.51	0.279
stan-k=510-sample_size=2700-lambda_spw=0.35-lambda_snh=400-lambda_inh=7	0.286
stan-k=1500-sample_size=2550-lambda_spw=0.4-lambda_snh=500-lambda_inh=6	0.287
stan-k=3000-sample_size=1000-lambda_spw=0.17-lambda_snh=350-lambda_inh=7	0.284
stan-k=530-sample_size=500-lambda_spw=0.81-lambda_snh=150-lambda_inh=0.54	0.282
stan-k=4500-sample_size=3000-lambda_spw=0.4-lambda_snh=300-lambda_inh=2	0.288
stan-k=1500-sample_size=2900-lambda_spw=0.14-lambda_snh=520-lambda_inh=2	0.285
stan-k=630-sample_size=2700-lambda_spw=0.7-lambda_snh=10-lambda_inh=6	0.288
stan-k=2800-sample_size=3000-lambda_spw=0.81-lambda_snh=150-lambda_inh=6	0.287

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.881
• Standard deviation: 0.006
• Maximum value: 0.898
• Minimum value: 0.869

Parameter/Metrics	MRR@20
stan-k=3500-sample_size=3000-lambda_spw=0.7-lambda_snh=250-lambda_inh=0.57	0.887
stan-k=530-sample_size=2000-lambda_spw=0.16-lambda_snh=520-lambda_inh=6	0.869
stan-k=630-sample_size=3000-lambda_spw=0.6-lambda_snh=100-lambda_inh=0.51	0.887
stan-k=570-sample_size=2700-lambda_spw=0.17-lambda_snh=25-lambda_inh=0.58	0.887
stan-k=5000-sample_size=1500-lambda_spw=0.13-lambda_snh=450-lambda_inh=20	0.877
stan-k=700-sample_size=2650-lambda_spw=0.1-lambda_snh=500-lambda_inh=7	0.873
stan-k=6000-sample_size=2800-lambda_spw=0.7-lambda_snh=400-lambda_inh=0.55	0.887
stan-k=2000-sample_size=2000-lambda_spw=0.4-lambda_snh=350-lambda_inh=2	0.880
stan-k=6000-sample_size=2800-lambda_spw=0.1-lambda_snh=200-lambda_inh=7	0.877
stan-k=5000-sample_size=2700-lambda_spw=0.1-lambda_snh=450-lambda_inh=0.58	0.881
stan-k=2500-sample_size=1500-lambda_spw=0.15-lambda_snh=250-lambda_inh=0.57	0.882
stan-k=570-sample_size=1000-lambda_spw=0.81-lambda_snh=350-lambda_inh=0.58	0.882
stan-k=2500-sample_size=2700-lambda_spw=0.16-lambda_snh=530-lambda_inh=7	0.877
stan-k=530-sample_size=2000-lambda_spw=0.1-lambda_snh=400-lambda_inh=0.57	0.874
stan-k=750-sample_size=1000-lambda_spw=0.6-lambda_snh=450-lambda_inh=0.51	0.886
stan-k=1500-sample_size=2800-lambda_spw=0.16-lambda_snh=10-lambda_inh=0.56	0.890
stan-k=570-sample_size=2650-lambda_spw=0.12-lambda_snh=530-lambda_inh=9	0.870
stan-k=5000-sample_size=2500-lambda_spw=0.15-lambda_snh=500-lambda_inh=1.5	0.878
stan-k=700-sample_size=2650-lambda_spw=0.81-lambda_snh=530-lambda_inh=20	0.882
stan-k=570-sample_size=1000-lambda_spw=0.16-lambda_snh=100-lambda_inh=0.56	0.884
stan-k=4000-sample_size=3000-lambda_spw=0.4-lambda_snh=450-lambda_inh=1.5	0.880
stan-k=630-sample_size=1500-lambda_spw=0.13-lambda_snh=200-lambda_inh=0.56	0.878
stan-k=2000-sample_size=3000-lambda_spw=0.35-lambda_snh=100-lambda_inh=2	0.881
stan-k=510-sample_size=1000-lambda_spw=0.6-lambda_snh=50-lambda_inh=0.51	0.888
stan-k=570-sample_size=2800-lambda_spw=0.6-lambda_snh=10-lambda_inh=1.5	0.893
stan-k=630-sample_size=2550-lambda_spw=0.81-lambda_snh=25-lambda_inh=6	0.891
stan-k=4000-sample_size=2900-lambda_spw=0.13-lambda_snh=400-lambda_inh=9	0.876
stan-k=4500-sample_size=2000-lambda_spw=0.4-lambda_snh=350-lambda_inh=0.55	0.882
stan-k=510-sample_size=2800-lambda_spw=0.81-lambda_snh=530-lambda_inh=6	0.874
stan-k=5500-sample_size=2800-lambda_spw=0.81-lambda_snh=300-lambda_inh=2	0.884
stan-k=6000-sample_size=500-lambda_spw=0.4-lambda_snh=250-lambda_inh=20	0.881
stan-k=2000-sample_size=1000-lambda_spw=0.15-lambda_snh=300-lambda_inh=15	0.878
stan-k=750-sample_size=2650-lambda_spw=0.13-lambda_snh=300-lambda_inh=0.56	0.878
stan-k=5000-sample_size=2500-lambda_spw=0.15-lambda_snh=300-lambda_inh=5	0.877
stan-k=2500-sample_size=2800-lambda_spw=0.35-lambda_snh=500-lambda_inh=0.58	0.882
stan-k=5000-sample_size=1000-lambda_spw=0.16-lambda_snh=50-lambda_inh=2	0.881
stan-k=700-sample_size=2500-lambda_spw=0.1-lambda_snh=25-lambda_inh=20	0.881
stan-k=3000-sample_size=1500-lambda_spw=0.35-lambda_snh=600-lambda_inh=15	0.880
stan-k=2500-sample_size=2800-lambda_spw=0.6-lambda_snh=470-lambda_inh=2	0.884
stan-k=2500-sample_size=2500-lambda_spw=0.12-lambda_snh=300-lambda_inh=0.52	0.881
stan-k=4500-sample_size=3000-lambda_spw=0.17-lambda_snh=400-lambda_inh=0.58	0.882
stan-k=6000-sample_size=2700-lambda_spw=0.1-lambda_snh=400-lambda_inh=0.56	0.881
stan-k=2800-sample_size=3000-lambda_spw=0.13-lambda_snh=50-lambda_inh=0.54	0.885
stan-k=2800-sample_size=500-lambda_spw=0.6-lambda_snh=10-lambda_inh=0.58	0.895
stan-k=5000-sample_size=2550-lambda_spw=0.81-lambda_snh=10-lambda_inh=20	0.898
stan-k=3500-sample_size=2700-lambda_spw=0.17-lambda_snh=25-lambda_inh=0.52	0.887
stan-k=4500-sample_size=2550-lambda_spw=0.35-lambda_snh=10-lambda_inh=2	0.887
stan-k=3000-sample_size=2650-lambda_spw=0.14-lambda_snh=150-lambda_inh=15	0.877
stan-k=4000-sample_size=2800-lambda_spw=0.13-lambda_snh=450-lambda_inh=0.53	0.881
stan-k=1500-sample_size=2500-lambda_spw=0.6-lambda_snh=500-lambda_inh=0.56	0.885
stan-k=3500-sample_size=2550-lambda_spw=0.7-lambda_snh=530-lambda_inh=0.51	0.887
stan-k=4000-sample_size=1500-lambda_spw=0.7-lambda_snh=250-lambda_inh=5	0.886
stan-k=530-sample_size=2550-lambda_spw=0.35-lambda_snh=450-lambda_inh=0.55	0.875
stan-k=700-sample_size=1000-lambda_spw=0.6-lambda_snh=250-lambda_inh=0.51	0.888
stan-k=1500-sample_size=2500-lambda_spw=0.12-lambda_snh=520-lambda_inh=0.56	0.881
stan-k=530-sample_size=2900-lambda_spw=0.15-lambda_snh=500-lambda_inh=5	0.869
stan-k=2800-sample_size=1500-lambda_spw=0.6-lambda_snh=520-lambda_inh=0.55	0.886
stan-k=510-sample_size=2650-lambda_spw=0.12-lambda_snh=450-lambda_inh=0.54	0.873
stan-k=2500-sample_size=3000-lambda_spw=0.4-lambda_snh=300-lambda_inh=9	0.880
stan-k=630-sample_size=1500-lambda_spw=0.6-lambda_snh=450-lambda_inh=6	0.876
stan-k=5000-sample_size=2700-lambda_spw=0.81-lambda_snh=250-lambda_inh=0.52	0.885
stan-k=5500-sample_size=2550-lambda_spw=0.16-lambda_snh=520-lambda_inh=2	0.877
stan-k=510-sample_size=3000-lambda_spw=0.15-lambda_snh=100-lambda_inh=5	0.879
stan-k=5500-sample_size=2800-lambda_spw=0.35-lambda_snh=25-lambda_inh=0.57	0.888
stan-k=510-sample_size=2800-lambda_spw=0.4-lambda_snh=500-lambda_inh=0.55	0.874
stan-k=600-sample_size=2700-lambda_spw=0.7-lambda_snh=250-lambda_inh=2	0.879
stan-k=570-sample_size=2800-lambda_spw=0.81-lambda_snh=100-lambda_inh=0.5	0.888
stan-k=4500-sample_size=1000-lambda_spw=0.6-lambda_snh=50-lambda_inh=5	0.887
stan-k=3000-sample_size=2550-lambda_spw=0.6-lambda_snh=300-lambda_inh=0.58	0.887
stan-k=700-sample_size=2550-lambda_spw=0.17-lambda_snh=25-lambda_inh=0.57	0.887
stan-k=750-sample_size=2500-lambda_spw=0.17-lambda_snh=500-lambda_inh=0.57	0.877
stan-k=510-sample_size=2900-lambda_spw=0.81-lambda_snh=520-lambda_inh=5	0.874
stan-k=6000-sample_size=2500-lambda_spw=0.16-lambda_snh=400-lambda_inh=0.55	0.882
stan-k=700-sample_size=2800-lambda_spw=0.16-lambda_snh=10-lambda_inh=0.5	0.889
stan-k=5500-sample_size=3000-lambda_spw=0.35-lambda_snh=100-lambda_inh=0.55	0.883
stan-k=5500-sample_size=2500-lambda_spw=0.12-lambda_snh=50-lambda_inh=9	0.878
stan-k=3500-sample_size=2900-lambda_spw=0.6-lambda_snh=150-lambda_inh=15	0.884
stan-k=2000-sample_size=2800-lambda_spw=0.13-lambda_snh=50-lambda_inh=9	0.878
stan-k=2500-sample_size=2650-lambda_spw=0.15-lambda_snh=25-lambda_inh=1	0.885
stan-k=6000-sample_size=1500-lambda_spw=0.35-lambda_snh=200-lambda_inh=0.51	0.883
stan-k=2500-sample_size=3000-lambda_spw=0.17-lambda_snh=600-lambda_inh=9	0.877
stan-k=510-sample_size=2650-lambda_spw=0.81-lambda_snh=25-lambda_inh=1	0.895
stan-k=5000-sample_size=500-lambda_spw=0.13-lambda_snh=530-lambda_inh=2	0.881
stan-k=5000-sample_size=3000-lambda_spw=0.81-lambda_snh=500-lambda_inh=2	0.884
stan-k=5000-sample_size=1500-lambda_spw=0.12-lambda_snh=450-lambda_inh=0.57	0.881
stan-k=4500-sample_size=2550-lambda_spw=0.4-lambda_snh=150-lambda_inh=2	0.881
stan-k=6000-sample_size=2000-lambda_spw=0.17-lambda_snh=400-lambda_inh=0.56	0.882
stan-k=530-sample_size=2800-lambda_spw=0.17-lambda_snh=200-lambda_inh=0.55	0.879
stan-k=600-sample_size=500-lambda_spw=0.15-lambda_snh=520-lambda_inh=15	0.878
stan-k=5000-sample_size=1500-lambda_spw=0.17-lambda_snh=10-lambda_inh=9	0.885
stan-k=630-sample_size=2000-lambda_spw=0.12-lambda_snh=520-lambda_inh=6	0.872
stan-k=570-sample_size=2650-lambda_spw=0.17-lambda_snh=530-lambda_inh=7	0.870
stan-k=4500-sample_size=2650-lambda_spw=0.14-lambda_snh=500-lambda_inh=0.57	0.881
stan-k=6000-sample_size=2900-lambda_spw=0.1-lambda_snh=450-lambda_inh=0.53	0.881
stan-k=4500-sample_size=2000-lambda_spw=0.13-lambda_snh=600-lambda_inh=7	0.877
stan-k=570-sample_size=2800-lambda_spw=0.15-lambda_snh=250-lambda_inh=1.5	0.874
stan-k=4500-sample_size=2900-lambda_spw=0.12-lambda_snh=200-lambda_inh=0.54	0.881
stan-k=5500-sample_size=2550-lambda_spw=0.12-lambda_snh=520-lambda_inh=9	0.876
stan-k=630-sample_size=2700-lambda_spw=0.14-lambda_snh=520-lambda_inh=0.57	0.875
stan-k=5500-sample_size=3000-lambda_spw=0.4-lambda_snh=50-lambda_inh=0.51	0.886

Hyperparameters for VSTAN

We tested the following hyperparameter space:

Parameter	Options
Number of Neighbors	[50, 100, 500, 600, 700, 800, 1000, 1300, 1500, 1700, 2000, 2500, 2800, 3000]
Sample Size	[500, 600, 800, 1000, 1800, 2500, 2200, 4000, 5000, 7000, 8000, 10000]
lambda_spw	[0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, 0.99, 0.11, 0.12, 0.101, 0.102, 0.103, 0.104, 0.105, 0.106, 0.107, 0.108, 0.15, 0.16, 1.2, 1.8, 2.4]
lambda_snh	[50,51, 55, 57, 71, 75, 80, 100, 150, 200, 400, 450, 470, 500, 520, 530, 600]
lambda_inh	[0.5, 0.51, 0.52, 0.53, 0.54, 0.55, 0.56, 0.57, 0.58, 1.8, 2, 2.4, 2.5, 2.8, 3, 3.5, 3.8, 4]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.380
• Standard deviation: 0.003
• Maximum value: 0.384
• Minimum value: 0.371

Parameters/Metrics	MRR@20
vstan-k=2000-sample_size=5400-lambda_spw=0.99-lambda_snh=250-lambda_inh=3.8-lambda_idf=12	0.378
vstan-k=1550-sample_size=5550-lambda_spw=0.107-lambda_snh=58-lambda_inh=3.4-lambda_idf=1	0.383
vstan-k=1000-sample_size=5600-lambda_spw=0.94-lambda_snh=51-lambda_inh=3.9-lambda_idf=1	0.380
vstan-k=3000-sample_size=5550-lambda_spw=0.108-lambda_snh=250-lambda_inh=3.9-lambda_idf=13	0.382
vstan-k=1550-sample_size=6000-lambda_spw=0.97-lambda_snh=58-lambda_inh=2.4-lambda_idf=15	0.378
vstan-k=1530-sample_size=5900-lambda_spw=0.92-lambda_snh=350-lambda_inh=1.8-lambda_idf=8	0.377
vstan-k=1500-sample_size=5400-lambda_spw=0.91-lambda_snh=55-lambda_inh=3.8-lambda_idf=2	0.380
vstan-k=3000-sample_size=5900-lambda_spw=0.97-lambda_snh=500-lambda_inh=3.9-lambda_idf=10	0.377
vstan-k=1000-sample_size=5500-lambda_spw=0.99-lambda_snh=500-lambda_inh=3.8-lambda_idf=14	0.377
vstan-k=2500-sample_size=5550-lambda_spw=0.105-lambda_snh=400-lambda_inh=1.3-lambda_idf=4	0.381
vstan-k=1600-sample_size=5750-lambda_spw=0.91-lambda_snh=200-lambda_inh=3.4-lambda_idf=8	0.378
vstan-k=1600-sample_size=5400-lambda_spw=0.102-lambda_snh=56-lambda_inh=1.5-lambda_idf=9	0.383
vstan-k=1200-sample_size=5400-lambda_spw=0.96-lambda_snh=58-lambda_inh=0.51-lambda_idf=3	0.373
vstan-k=1200-sample_size=5750-lambda_spw=0.94-lambda_snh=400-lambda_inh=1.8-lambda_idf=1	0.376
vstan-k=1200-sample_size=5500-lambda_spw=0.108-lambda_snh=300-lambda_inh=3.8-lambda_idf=12	0.382
vstan-k=1520-sample_size=5800-lambda_spw=0.91-lambda_snh=200-lambda_inh=1.8-lambda_idf=8	0.376
vstan-k=1550-sample_size=5900-lambda_spw=0.108-lambda_snh=58-lambda_inh=3.4-lambda_idf=15	0.383
vstan-k=1000-sample_size=5500-lambda_spw=0.104-lambda_snh=56-lambda_inh=1.5-lambda_idf=7	0.383
vstan-k=1570-sample_size=5750-lambda_spw=0.103-lambda_snh=56-lambda_inh=3.8-lambda_idf=5	0.383
vstan-k=2000-sample_size=5650-lambda_spw=0.91-lambda_snh=56-lambda_inh=2.4-lambda_idf=4	0.378
vstan-k=1570-sample_size=5600-lambda_spw=0.106-lambda_snh=400-lambda_inh=1.3-lambda_idf=5	0.381
vstan-k=2000-sample_size=6000-lambda_spw=0.107-lambda_snh=59-lambda_inh=3.8-lambda_idf=6	0.383
vstan-k=1520-sample_size=6000-lambda_spw=0.101-lambda_snh=200-lambda_inh=1.3-lambda_idf=12	0.382
vstan-k=2500-sample_size=5600-lambda_spw=0.107-lambda_snh=250-lambda_inh=1.5-lambda_idf=1	0.381
vstan-k=1560-sample_size=6000-lambda_spw=0.99-lambda_snh=55-lambda_inh=3.4-lambda_idf=9	0.379
vstan-k=1500-sample_size=5600-lambda_spw=0.96-lambda_snh=300-lambda_inh=1.8-lambda_idf=5	0.376
vstan-k=1500-sample_size=5600-lambda_spw=0.93-lambda_snh=200-lambda_inh=3.4-lambda_idf=7	0.378
vstan-k=1510-sample_size=5400-lambda_spw=0.96-lambda_snh=450-lambda_inh=3.4-lambda_idf=7	0.378
vstan-k=1550-sample_size=5750-lambda_spw=0.92-lambda_snh=300-lambda_inh=1.8-lambda_idf=14	0.376
vstan-k=1520-sample_size=5800-lambda_spw=0.92-lambda_snh=500-lambda_inh=1.3-lambda_idf=11	0.374
vstan-k=2000-sample_size=5600-lambda_spw=0.99-lambda_snh=50-lambda_inh=3.8-lambda_idf=15	0.379
vstan-k=2000-sample_size=5500-lambda_spw=0.104-lambda_snh=53-lambda_inh=2.4-lambda_idf=1	0.384
vstan-k=1600-sample_size=5550-lambda_spw=0.108-lambda_snh=450-lambda_inh=0.51-lambda_idf=13	0.379
vstan-k=1570-sample_size=5550-lambda_spw=0.106-lambda_snh=500-lambda_inh=3.8-lambda_idf=12	0.381
vstan-k=2500-sample_size=5500-lambda_spw=0.101-lambda_snh=57-lambda_inh=3.8-lambda_idf=2	0.383
vstan-k=2500-sample_size=6000-lambda_spw=0.106-lambda_snh=400-lambda_inh=2.4-lambda_idf=13	0.382
vstan-k=3000-sample_size=5650-lambda_spw=0.94-lambda_snh=53-lambda_inh=0.51-lambda_idf=9	0.374
vstan-k=3000-sample_size=5550-lambda_spw=0.92-lambda_snh=56-lambda_inh=2.4-lambda_idf=10	0.378
vstan-k=1520-sample_size=5650-lambda_spw=0.11-lambda_snh=53-lambda_inh=3.9-lambda_idf=5	0.383
vstan-k=1500-sample_size=5600-lambda_spw=0.109-lambda_snh=55-lambda_inh=3.4-lambda_idf=1	0.384
vstan-k=2500-sample_size=5650-lambda_spw=0.108-lambda_snh=58-lambda_inh=1.8-lambda_idf=15	0.384
vstan-k=1400-sample_size=5600-lambda_spw=0.97-lambda_snh=200-lambda_inh=3.9-lambda_idf=3	0.378
vstan-k=3000-sample_size=5600-lambda_spw=0.101-lambda_snh=54-lambda_inh=1.3-lambda_idf=10	0.383
vstan-k=1530-sample_size=5550-lambda_spw=0.92-lambda_snh=53-lambda_inh=3.9-lambda_idf=14	0.379
vstan-k=2000-sample_size=5600-lambda_spw=0.106-lambda_snh=400-lambda_inh=2.4-lambda_idf=8	0.382
vstan-k=1570-sample_size=5550-lambda_spw=0.94-lambda_snh=55-lambda_inh=1.5-lambda_idf=4	0.377
vstan-k=3000-sample_size=5550-lambda_spw=0.104-lambda_snh=53-lambda_inh=3.9-lambda_idf=6	0.383
vstan-k=1550-sample_size=5600-lambda_spw=0.108-lambda_snh=400-lambda_inh=3.9-lambda_idf=11	0.381
vstan-k=1550-sample_size=5400-lambda_spw=0.108-lambda_snh=500-lambda_inh=2.4-lambda_idf=4	0.382
vstan-k=2500-sample_size=5900-lambda_spw=0.91-lambda_snh=57-lambda_inh=1.5-lambda_idf=10	0.377
vstan-k=1550-sample_size=5650-lambda_spw=0.96-lambda_snh=350-lambda_inh=1.5-lambda_idf=6	0.375
vstan-k=1530-sample_size=5800-lambda_spw=0.96-lambda_snh=450-lambda_inh=1.3-lambda_idf=2	0.375
vstan-k=1550-sample_size=6000-lambda_spw=0.108-lambda_snh=400-lambda_inh=1.8-lambda_idf=13	0.382
vstan-k=2500-sample_size=5800-lambda_spw=0.93-lambda_snh=450-lambda_inh=1.5-lambda_idf=9	0.375
vstan-k=1550-sample_size=6000-lambda_spw=0.107-lambda_snh=350-lambda_inh=3.4-lambda_idf=11	0.382
vstan-k=1540-sample_size=5650-lambda_spw=0.102-lambda_snh=54-lambda_inh=1.8-lambda_idf=13	0.384
vstan-k=1000-sample_size=5400-lambda_spw=0.104-lambda_snh=52-lambda_inh=1.8-lambda_idf=10	0.384
vstan-k=1600-sample_size=5750-lambda_spw=0.11-lambda_snh=55-lambda_inh=2.4-lambda_idf=13	0.384
vstan-k=1520-sample_size=5500-lambda_spw=0.109-lambda_snh=60-lambda_inh=1.3-lambda_idf=15	0.383
vstan-k=1540-sample_size=5500-lambda_spw=0.109-lambda_snh=450-lambda_inh=3.8-lambda_idf=2	0.382
vstan-k=1550-sample_size=5900-lambda_spw=0.94-lambda_snh=52-lambda_inh=1.3-lambda_idf=9	0.377
vstan-k=1000-sample_size=5400-lambda_spw=0.106-lambda_snh=350-lambda_inh=1.3-lambda_idf=1	0.381
vstan-k=1600-sample_size=5600-lambda_spw=0.101-lambda_snh=53-lambda_inh=1.3-lambda_idf=4	0.383
vstan-k=1400-sample_size=5500-lambda_spw=0.94-lambda_snh=500-lambda_inh=0.51-lambda_idf=2	0.371
vstan-k=1200-sample_size=5650-lambda_spw=0.109-lambda_snh=53-lambda_inh=1.5-lambda_idf=10	0.384
vstan-k=1550-sample_size=6000-lambda_spw=0.103-lambda_snh=400-lambda_inh=1.8-lambda_idf=9	0.382
vstan-k=1550-sample_size=5650-lambda_spw=0.95-lambda_snh=350-lambda_inh=1.5-lambda_idf=4	0.375
vstan-k=2500-sample_size=5550-lambda_spw=0.102-lambda_snh=52-lambda_inh=0.51-lambda_idf=15	0.382
vstan-k=1500-sample_size=5650-lambda_spw=0.109-lambda_snh=58-lambda_inh=1.3-lambda_idf=13	0.383
vstan-k=1550-sample_size=5750-lambda_spw=0.96-lambda_snh=55-lambda_inh=2.4-lambda_idf=15	0.378
vstan-k=1570-sample_size=5600-lambda_spw=0.96-lambda_snh=57-lambda_inh=3.4-lambda_idf=11	0.379
vstan-k=2500-sample_size=5800-lambda_spw=0.106-lambda_snh=58-lambda_inh=0.51-lambda_idf=2	0.381
vstan-k=1510-sample_size=5400-lambda_spw=0.96-lambda_snh=350-lambda_inh=1.5-lambda_idf=7	0.375
vstan-k=3000-sample_size=5400-lambda_spw=0.98-lambda_snh=250-lambda_inh=1.5-lambda_idf=1	0.375
vstan-k=1200-sample_size=5650-lambda_spw=0.98-lambda_snh=53-lambda_inh=3.4-lambda_idf=8	0.379
vstan-k=1550-sample_size=5400-lambda_spw=0.96-lambda_snh=56-lambda_inh=2.4-lambda_idf=2	0.378
vstan-k=1520-sample_size=5400-lambda_spw=0.102-lambda_snh=54-lambda_inh=1.3-lambda_idf=3	0.383
vstan-k=1520-sample_size=5600-lambda_spw=0.93-lambda_snh=59-lambda_inh=3.9-lambda_idf=3	0.379
vstan-k=1560-sample_size=5400-lambda_spw=0.93-lambda_snh=200-lambda_inh=0.51-lambda_idf=14	0.372
vstan-k=1560-sample_size=5500-lambda_spw=0.104-lambda_snh=50-lambda_inh=0.51-lambda_idf=8	0.380
vstan-k=3000-sample_size=5400-lambda_spw=0.99-lambda_snh=54-lambda_inh=2.4-lambda_idf=7	0.378
vstan-k=1530-sample_size=5900-lambda_spw=0.94-lambda_snh=55-lambda_inh=3.4-lambda_idf=11	0.379
vstan-k=3000-sample_size=5400-lambda_spw=0.101-lambda_snh=54-lambda_inh=3.8-lambda_idf=1	0.383
vstan-k=1550-sample_size=5800-lambda_spw=0.93-lambda_snh=54-lambda_inh=0.51-lambda_idf=9	0.373
vstan-k=1510-sample_size=5900-lambda_spw=0.99-lambda_snh=59-lambda_inh=3.4-lambda_idf=15	0.379
vstan-k=1600-sample_size=5650-lambda_spw=0.102-lambda_snh=500-lambda_inh=1.5-lambda_idf=5	0.380
vstan-k=1000-sample_size=5400-lambda_spw=0.101-lambda_snh=300-lambda_inh=1.5-lambda_idf=9	0.381
vstan-k=1400-sample_size=5500-lambda_spw=0.94-lambda_snh=54-lambda_inh=1.5-lambda_idf=3	0.377
vstan-k=1600-sample_size=5500-lambda_spw=0.103-lambda_snh=53-lambda_inh=3.9-lambda_idf=9	0.383
vstan-k=1550-sample_size=5600-lambda_spw=0.107-lambda_snh=54-lambda_inh=3.8-lambda_idf=12	0.384
vstan-k=1550-sample_size=6000-lambda_spw=0.93-lambda_snh=55-lambda_inh=3.8-lambda_idf=10	0.379
vstan-k=1600-sample_size=5750-lambda_spw=0.95-lambda_snh=50-lambda_inh=2.4-lambda_idf=13	0.379
vstan-k=1550-sample_size=5500-lambda_spw=0.98-lambda_snh=400-lambda_inh=1.5-lambda_idf=7	0.375
vstan-k=1510-sample_size=5600-lambda_spw=0.106-lambda_snh=400-lambda_inh=3.4-lambda_idf=8	0.382
vstan-k=1000-sample_size=5400-lambda_spw=0.92-lambda_snh=350-lambda_inh=1.3-lambda_idf=15	0.375
vstan-k=1500-sample_size=5500-lambda_spw=0.104-lambda_snh=54-lambda_inh=1.8-lambda_idf=13	0.384
vstan-k=3000-sample_size=5900-lambda_spw=0.94-lambda_snh=57-lambda_inh=1.5-lambda_idf=13	0.377
vstan-k=1500-sample_size=5750-lambda_spw=0.99-lambda_snh=55-lambda_inh=3.8-lambda_idf=1	0.379
vstan-k=1570-sample_size=5900-lambda_spw=0.106-lambda_snh=400-lambda_inh=2.4-lambda_idf=11	0.382
vstan-k=1540-sample_size=5400-lambda_spw=0.98-lambda_snh=53-lambda_inh=2.4-lambda_idf=14	0.378
vstan-k=1500-sample_size=5500-lambda_spw=0.11-lambda_snh=25-lambda_inh=3.9-lambda_idf=15	0.385

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.284
• Standard deviation: 0.003
• Maximum value: 0.293
• Minimum value: 0.282

Parameters/Metrics	MRR@20
vstan-k=2500-sample_size=6000-lambda_spw=0.95-lambda_snh=50-lambda_inh=3.4-lambda_idf=3	0.290
vstan-k=1200-sample_size=5650-lambda_spw=0.91-lambda_snh=350-lambda_inh=3.9-lambda_idf=13	0.290
vstan-k=1510-sample_size=5400-lambda_spw=0.106-lambda_snh=53-lambda_inh=1.3-lambda_idf=14	0.287
vstan-k=1200-sample_size=5550-lambda_spw=0.93-lambda_snh=55-lambda_inh=3.8-lambda_idf=6	0.290
vstan-k=1550-sample_size=5500-lambda_spw=0.99-lambda_snh=52-lambda_inh=3.8-lambda_idf=9	0.290
vstan-k=1000-sample_size=5500-lambda_spw=0.109-lambda_snh=300-lambda_inh=1.5-lambda_idf=1	0.287
vstan-k=1000-sample_size=6000-lambda_spw=0.93-lambda_snh=54-lambda_inh=3.8-lambda_idf=15	0.290
vstan-k=1500-sample_size=5900-lambda_spw=0.96-lambda_snh=54-lambda_inh=0.51-lambda_idf=14	0.282
vstan-k=1530-sample_size=5800-lambda_spw=0.109-lambda_snh=300-lambda_inh=3.4-lambda_idf=14	0.285
vstan-k=1520-sample_size=5600-lambda_spw=0.106-lambda_snh=200-lambda_inh=3.9-lambda_idf=4	0.286
vstan-k=3000-sample_size=6000-lambda_spw=0.91-lambda_snh=52-lambda_inh=1.5-lambda_idf=2	0.290
vstan-k=1400-sample_size=5650-lambda_spw=0.95-lambda_snh=500-lambda_inh=0.51-lambda_idf=10	0.282
vstan-k=1500-sample_size=5400-lambda_spw=0.97-lambda_snh=54-lambda_inh=3.8-lambda_idf=12	0.290
vstan-k=1540-sample_size=5500-lambda_spw=0.99-lambda_snh=56-lambda_inh=3.8-lambda_idf=14	0.290
vstan-k=1520-sample_size=5400-lambda_spw=0.92-lambda_snh=57-lambda_inh=1.3-lambda_idf=4	0.291
vstan-k=2000-sample_size=5650-lambda_spw=0.99-lambda_snh=51-lambda_inh=1.8-lambda_idf=6	0.290
vstan-k=2000-sample_size=5550-lambda_spw=0.11-lambda_snh=400-lambda_inh=3.4-lambda_idf=12	0.285
vstan-k=1000-sample_size=5600-lambda_spw=0.107-lambda_snh=52-lambda_inh=2.4-lambda_idf=5	0.285
vstan-k=2000-sample_size=6000-lambda_spw=0.105-lambda_snh=59-lambda_inh=3.4-lambda_idf=4	0.285
vstan-k=1540-sample_size=5900-lambda_spw=0.92-lambda_snh=250-lambda_inh=1.3-lambda_idf=5	0.291
vstan-k=1560-sample_size=5900-lambda_spw=0.102-lambda_snh=57-lambda_inh=1.5-lambda_idf=10	0.287
vstan-k=1530-sample_size=5400-lambda_spw=0.97-lambda_snh=56-lambda_inh=1.3-lambda_idf=1	0.291
vstan-k=2500-sample_size=5800-lambda_spw=0.99-lambda_snh=51-lambda_inh=2.4-lambda_idf=13	0.292
vstan-k=1200-sample_size=5400-lambda_spw=0.94-lambda_snh=55-lambda_inh=2.4-lambda_idf=11	0.291
vstan-k=1510-sample_size=5600-lambda_spw=0.97-lambda_snh=56-lambda_inh=1.5-lambda_idf=3	0.290
vstan-k=1540-sample_size=6000-lambda_spw=0.106-lambda_snh=59-lambda_inh=3.9-lambda_idf=5	0.286
vstan-k=1400-sample_size=5550-lambda_spw=0.109-lambda_snh=53-lambda_inh=2.4-lambda_idf=3	0.285
vstan-k=1570-sample_size=5600-lambda_spw=0.98-lambda_snh=51-lambda_inh=3.4-lambda_idf=14	0.291
vstan-k=1500-sample_size=5400-lambda_spw=0.11-lambda_snh=350-lambda_inh=3.9-lambda_idf=6	0.286
vstan-k=1400-sample_size=5800-lambda_spw=0.102-lambda_snh=450-lambda_inh=1.3-lambda_idf=5	0.288
vstan-k=1550-sample_size=5750-lambda_spw=0.101-lambda_snh=500-lambda_inh=0.51-lambda_idf=5	0.284
vstan-k=1550-sample_size=5650-lambda_spw=0.96-lambda_snh=300-lambda_inh=3.4-lambda_idf=14	0.290
vstan-k=1520-sample_size=5400-lambda_spw=0.103-lambda_snh=200-lambda_inh=1.5-lambda_idf=8	0.287
vstan-k=3000-sample_size=6000-lambda_spw=0.92-lambda_snh=60-lambda_inh=2.4-lambda_idf=15	0.291
vstan-k=1530-sample_size=5650-lambda_spw=0.107-lambda_snh=250-lambda_inh=1.8-lambda_idf=11	0.285
vstan-k=3000-sample_size=5650-lambda_spw=0.94-lambda_snh=450-lambda_inh=3.9-lambda_idf=9	0.290
vstan-k=1400-sample_size=6000-lambda_spw=0.105-lambda_snh=55-lambda_inh=1.5-lambda_idf=10	0.287
vstan-k=1550-sample_size=5650-lambda_spw=0.107-lambda_snh=55-lambda_inh=2.4-lambda_idf=15	0.286
vstan-k=1500-sample_size=5600-lambda_spw=0.95-lambda_snh=57-lambda_inh=3.8-lambda_idf=4	0.289
vstan-k=1560-sample_size=5900-lambda_spw=0.103-lambda_snh=250-lambda_inh=3.9-lambda_idf=2	0.286
vstan-k=1540-sample_size=5400-lambda_spw=0.99-lambda_snh=52-lambda_inh=3.4-lambda_idf=12	0.291
vstan-k=1530-sample_size=6000-lambda_spw=0.107-lambda_snh=300-lambda_inh=1.8-lambda_idf=9	0.285
vstan-k=1400-sample_size=5500-lambda_spw=0.101-lambda_snh=55-lambda_inh=1.8-lambda_idf=2	0.286
vstan-k=1600-sample_size=5650-lambda_spw=0.106-lambda_snh=200-lambda_inh=1.5-lambda_idf=6	0.287
vstan-k=1570-sample_size=5900-lambda_spw=0.91-lambda_snh=58-lambda_inh=3.8-lambda_idf=10	0.290
vstan-k=1550-sample_size=5550-lambda_spw=0.107-lambda_snh=50-lambda_inh=0.51-lambda_idf=7	0.284
vstan-k=2000-sample_size=5750-lambda_spw=0.105-lambda_snh=51-lambda_inh=3.8-lambda_idf=6	0.285
vstan-k=3000-sample_size=5550-lambda_spw=0.98-lambda_snh=200-lambda_inh=1.5-lambda_idf=5	0.290
vstan-k=1550-sample_size=5900-lambda_spw=0.91-lambda_snh=50-lambda_inh=3.4-lambda_idf=4	0.290
vstan-k=1600-sample_size=6000-lambda_spw=0.103-lambda_snh=350-lambda_inh=3.8-lambda_idf=9	0.286
vstan-k=1500-sample_size=5800-lambda_spw=0.101-lambda_snh=55-lambda_inh=0.51-lambda_idf=1	0.284
vstan-k=1600-sample_size=5900-lambda_spw=0.95-lambda_snh=500-lambda_inh=3.4-lambda_idf=9	0.290
vstan-k=2000-sample_size=5900-lambda_spw=0.109-lambda_snh=250-lambda_inh=1.5-lambda_idf=14	0.287
vstan-k=2000-sample_size=5400-lambda_spw=0.96-lambda_snh=500-lambda_inh=1.3-lambda_idf=9	0.291
vstan-k=1510-sample_size=5500-lambda_spw=0.99-lambda_snh=50-lambda_inh=3.8-lambda_idf=9	0.290
vstan-k=2500-sample_size=5900-lambda_spw=0.99-lambda_snh=300-lambda_inh=3.4-lambda_idf=2	0.291
vstan-k=1530-sample_size=5750-lambda_spw=0.101-lambda_snh=57-lambda_inh=3.4-lambda_idf=8	0.285
vstan-k=1550-sample_size=6000-lambda_spw=0.104-lambda_snh=57-lambda_inh=1.5-lambda_idf=8	0.287
vstan-k=1550-sample_size=5500-lambda_spw=0.93-lambda_snh=52-lambda_inh=1.3-lambda_idf=14	0.290
vstan-k=1530-sample_size=5400-lambda_spw=0.92-lambda_snh=56-lambda_inh=0.51-lambda_idf=2	0.282
vstan-k=1500-sample_size=5600-lambda_spw=0.105-lambda_snh=52-lambda_inh=3.9-lambda_idf=15	0.286
vstan-k=1510-sample_size=5650-lambda_spw=0.96-lambda_snh=56-lambda_inh=0.51-lambda_idf=7	0.282
vstan-k=1600-sample_size=5500-lambda_spw=0.99-lambda_snh=59-lambda_inh=3.9-lambda_idf=14	0.290
vstan-k=1570-sample_size=5550-lambda_spw=0.97-lambda_snh=56-lambda_inh=3.9-lambda_idf=8	0.289
vstan-k=1530-sample_size=5600-lambda_spw=0.98-lambda_snh=300-lambda_inh=2.4-lambda_idf=6	0.293
vstan-k=1400-sample_size=6000-lambda_spw=0.107-lambda_snh=200-lambda_inh=0.51-lambda_idf=3	0.284
vstan-k=2500-sample_size=5900-lambda_spw=0.102-lambda_snh=55-lambda_inh=3.8-lambda_idf=3	0.286
vstan-k=1530-sample_size=5650-lambda_spw=0.94-lambda_snh=350-lambda_inh=3.9-lambda_idf=2	0.291
vstan-k=1000-sample_size=5650-lambda_spw=0.108-lambda_snh=53-lambda_inh=3.8-lambda_idf=7	0.285
vstan-k=1530-sample_size=5500-lambda_spw=0.103-lambda_snh=350-lambda_inh=1.8-lambda_idf=2	0.286
vstan-k=1200-sample_size=5750-lambda_spw=0.99-lambda_snh=300-lambda_inh=3.4-lambda_idf=3	0.291
vstan-k=1400-sample_size=6000-lambda_spw=0.93-lambda_snh=55-lambda_inh=3.8-lambda_idf=12	0.290
vstan-k=1500-sample_size=5650-lambda_spw=0.102-lambda_snh=450-lambda_inh=1.8-lambda_idf=2	0.286
vstan-k=1520-sample_size=5500-lambda_spw=0.11-lambda_snh=57-lambda_inh=1.3-lambda_idf=11	0.287
vstan-k=1540-sample_size=5550-lambda_spw=0.94-lambda_snh=59-lambda_inh=1.5-lambda_idf=2	0.290
vstan-k=1550-sample_size=5550-lambda_spw=0.105-lambda_snh=52-lambda_inh=3.8-lambda_idf=2	0.286
vstan-k=1500-sample_size=5750-lambda_spw=0.104-lambda_snh=53-lambda_inh=1.5-lambda_idf=10	0.287
vstan-k=1570-sample_size=5550-lambda_spw=0.105-lambda_snh=200-lambda_inh=3.4-lambda_idf=10	0.285
vstan-k=2000-sample_size=5600-lambda_spw=0.103-lambda_snh=300-lambda_inh=3.4-lambda_idf=12	0.285
vstan-k=1530-sample_size=5400-lambda_spw=0.93-lambda_snh=58-lambda_inh=3.4-lambda_idf=6	0.290
vstan-k=1550-sample_size=5550-lambda_spw=0.103-lambda_snh=400-lambda_inh=1.8-lambda_idf=3	0.286
vstan-k=2000-sample_size=5650-lambda_spw=0.108-lambda_snh=59-lambda_inh=3.8-lambda_idf=1	0.286
vstan-k=1000-sample_size=5550-lambda_spw=0.108-lambda_snh=250-lambda_inh=3.4-lambda_idf=4	0.285
vstan-k=1530-sample_size=5400-lambda_spw=0.101-lambda_snh=59-lambda_inh=1.3-lambda_idf=9	0.287
vstan-k=1510-sample_size=5400-lambda_spw=0.91-lambda_snh=51-lambda_inh=1.5-lambda_idf=9	0.290
vstan-k=1500-sample_size=5550-lambda_spw=0.97-lambda_snh=450-lambda_inh=0.51-lambda_idf=5	0.282
vstan-k=3000-sample_size=5800-lambda_spw=0.91-lambda_snh=350-lambda_inh=3.9-lambda_idf=2	0.290
vstan-k=1500-sample_size=5650-lambda_spw=0.101-lambda_snh=58-lambda_inh=1.5-lambda_idf=13	0.287
vstan-k=1000-sample_size=5550-lambda_spw=0.92-lambda_snh=400-lambda_inh=3.4-lambda_idf=10	0.290
vstan-k=1550-sample_size=6000-lambda_spw=0.94-lambda_snh=350-lambda_inh=1.5-lambda_idf=1	0.290
vstan-k=1500-sample_size=5600-lambda_spw=0.107-lambda_snh=200-lambda_inh=0.51-lambda_idf=7	0.284
vstan-k=1560-sample_size=6000-lambda_spw=0.109-lambda_snh=450-lambda_inh=1.3-lambda_idf=5	0.288
vstan-k=1540-sample_size=5500-lambda_spw=0.102-lambda_snh=250-lambda_inh=1.5-lambda_idf=8	0.287
vstan-k=1550-sample_size=5400-lambda_spw=0.95-lambda_snh=56-lambda_inh=2.4-lambda_idf=1	0.293
vstan-k=1530-sample_size=5800-lambda_spw=0.109-lambda_snh=53-lambda_inh=3.4-lambda_idf=9	0.285
vstan-k=3000-sample_size=5400-lambda_spw=0.109-lambda_snh=59-lambda_inh=3.9-lambda_idf=9	0.286
vstan-k=1550-sample_size=5550-lambda_spw=0.104-lambda_snh=250-lambda_inh=1.3-lambda_idf=14	0.287
vstan-k=1200-sample_size=5600-lambda_spw=0.98-lambda_snh=58-lambda_inh=2.4-lambda_idf=7	0.292
vstan-k=1510-sample_size=5650-lambda_spw=0.101-lambda_snh=55-lambda_inh=0.51-lambda_idf=6	0.284
vstan-k=1560-sample_size=5800-lambda_spw=0.98-lambda_snh=450-lambda_inh=0.51-lambda_idf=13	0.282
vstan-k=2000-sample_size=3000-lambda_spw=0.98-lambda_snh=20-lambda_inh=2.4-lambda_idf=30	0.291

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.881
• Standard deviation: 0.004
• Maximum value: 0.907
• Minimum value: 0.875

Parameters/Metrics	MRR@20
vstan-k=1570-sample_size=6000-lambda_spw=0.11-lambda_snh=450-lambda_inh=0.51-lambda_idf=1	0.878
vstan-k=1000-sample_size=5600-lambda_spw=0.105-lambda_snh=58-lambda_inh=3.4-lambda_idf=5	0.881
vstan-k=1560-sample_size=5400-lambda_spw=0.97-lambda_snh=400-lambda_inh=3.4-lambda_idf=7	0.879
vstan-k=1400-sample_size=5550-lambda_spw=0.106-lambda_snh=51-lambda_inh=3.4-lambda_idf=1	0.880
vstan-k=1510-sample_size=5750-lambda_spw=0.104-lambda_snh=51-lambda_inh=3.8-lambda_idf=10	0.881
vstan-k=1530-sample_size=5550-lambda_spw=0.11-lambda_snh=54-lambda_inh=1.8-lambda_idf=4	0.881
vstan-k=1550-sample_size=5800-lambda_spw=0.99-lambda_snh=57-lambda_inh=2.4-lambda_idf=8	0.884
vstan-k=1000-sample_size=5500-lambda_spw=0.95-lambda_snh=59-lambda_inh=1.5-lambda_idf=6	0.885
vstan-k=3000-sample_size=5900-lambda_spw=0.93-lambda_snh=52-lambda_inh=3.8-lambda_idf=8	0.884
vstan-k=2000-sample_size=5650-lambda_spw=0.11-lambda_snh=53-lambda_inh=1.3-lambda_idf=8	0.881
vstan-k=1550-sample_size=5800-lambda_spw=0.91-lambda_snh=250-lambda_inh=1.5-lambda_idf=1	0.879
vstan-k=1560-sample_size=5400-lambda_spw=0.93-lambda_snh=200-lambda_inh=2.4-lambda_idf=5	0.883
vstan-k=1500-sample_size=5600-lambda_spw=0.101-lambda_snh=50-lambda_inh=2.4-lambda_idf=1	0.881
vstan-k=2000-sample_size=5750-lambda_spw=0.105-lambda_snh=54-lambda_inh=1.5-lambda_idf=3	0.881
vstan-k=1510-sample_size=5800-lambda_spw=0.104-lambda_snh=58-lambda_inh=2.4-lambda_idf=6	0.881
vstan-k=1600-sample_size=6000-lambda_spw=0.94-lambda_snh=500-lambda_inh=3.8-lambda_idf=15	0.878
vstan-k=1570-sample_size=5650-lambda_spw=0.102-lambda_snh=54-lambda_inh=3.4-lambda_idf=4	0.881
vstan-k=1530-sample_size=5650-lambda_spw=0.11-lambda_snh=52-lambda_inh=3.4-lambda_idf=14	0.881
vstan-k=1400-sample_size=5550-lambda_spw=0.105-lambda_snh=250-lambda_inh=1.5-lambda_idf=11	0.876
vstan-k=3000-sample_size=5500-lambda_spw=0.91-lambda_snh=300-lambda_inh=1.3-lambda_idf=11	0.881
vstan-k=2500-sample_size=5800-lambda_spw=0.105-lambda_snh=58-lambda_inh=3.8-lambda_idf=2	0.881
vstan-k=1550-sample_size=5750-lambda_spw=0.104-lambda_snh=51-lambda_inh=3.8-lambda_idf=11	0.881
vstan-k=3000-sample_size=5550-lambda_spw=0.91-lambda_snh=350-lambda_inh=3.8-lambda_idf=3	0.881
vstan-k=1600-sample_size=5750-lambda_spw=0.105-lambda_snh=500-lambda_inh=1.3-lambda_idf=13	0.875
vstan-k=1600-sample_size=5550-lambda_spw=0.99-lambda_snh=400-lambda_inh=3.9-lambda_idf=6	0.879
vstan-k=3000-sample_size=5600-lambda_spw=0.107-lambda_snh=450-lambda_inh=3.8-lambda_idf=3	0.878
vstan-k=1510-sample_size=5900-lambda_spw=0.95-lambda_snh=54-lambda_inh=1.3-lambda_idf=10	0.885
vstan-k=1550-sample_size=6000-lambda_spw=0.94-lambda_snh=500-lambda_inh=2.4-lambda_idf=10	0.878
vstan-k=1550-sample_size=5800-lambda_spw=0.97-lambda_snh=53-lambda_inh=3.9-lambda_idf=15	0.884
vstan-k=1200-sample_size=5650-lambda_spw=0.11-lambda_snh=53-lambda_inh=1.5-lambda_idf=5	0.881
vstan-k=1500-sample_size=5550-lambda_spw=0.11-lambda_snh=50-lambda_inh=1.5-lambda_idf=14	0.882
vstan-k=1530-sample_size=5650-lambda_spw=0.94-lambda_snh=400-lambda_inh=1.8-lambda_idf=12	0.878
vstan-k=2000-sample_size=5750-lambda_spw=0.91-lambda_snh=56-lambda_inh=3.8-lambda_idf=13	0.884
vstan-k=1500-sample_size=5400-lambda_spw=0.103-lambda_snh=60-lambda_inh=1.5-lambda_idf=3	0.881
vstan-k=1540-sample_size=5750-lambda_spw=0.11-lambda_snh=350-lambda_inh=3.9-lambda_idf=2	0.875
vstan-k=1570-sample_size=5900-lambda_spw=0.105-lambda_snh=56-lambda_inh=0.51-lambda_idf=8	0.887
vstan-k=2000-sample_size=5550-lambda_spw=0.101-lambda_snh=50-lambda_inh=3.9-lambda_idf=14	0.881
vstan-k=1600-sample_size=5900-lambda_spw=0.96-lambda_snh=57-lambda_inh=0.51-lambda_idf=15	0.887
vstan-k=3000-sample_size=6000-lambda_spw=0.108-lambda_snh=500-lambda_inh=1.5-lambda_idf=3	0.878
vstan-k=1000-sample_size=5650-lambda_spw=0.94-lambda_snh=500-lambda_inh=1.8-lambda_idf=14	0.877
vstan-k=1540-sample_size=5750-lambda_spw=0.94-lambda_snh=59-lambda_inh=1.3-lambda_idf=8	0.885
vstan-k=1200-sample_size=5500-lambda_spw=0.92-lambda_snh=56-lambda_inh=1.5-lambda_idf=6	0.885
vstan-k=2500-sample_size=6000-lambda_spw=0.103-lambda_snh=54-lambda_inh=0.51-lambda_idf=5	0.886
vstan-k=1540-sample_size=5500-lambda_spw=0.95-lambda_snh=56-lambda_inh=3.4-lambda_idf=9	0.884
vstan-k=2000-sample_size=5600-lambda_spw=0.108-lambda_snh=450-lambda_inh=0.51-lambda_idf=2	0.878
vstan-k=1540-sample_size=5650-lambda_spw=0.101-lambda_snh=300-lambda_inh=3.4-lambda_idf=3	0.876
vstan-k=1510-sample_size=5400-lambda_spw=0.93-lambda_snh=55-lambda_inh=3.9-lambda_idf=15	0.884
vstan-k=1500-sample_size=5500-lambda_spw=0.104-lambda_snh=500-lambda_inh=1.5-lambda_idf=8	0.875
vstan-k=1550-sample_size=5550-lambda_spw=0.98-lambda_snh=53-lambda_inh=1.5-lambda_idf=3	0.885
vstan-k=1500-sample_size=5500-lambda_spw=0.99-lambda_snh=52-lambda_inh=1.5-lambda_idf=11	0.885
vstan-k=2000-sample_size=5500-lambda_spw=0.95-lambda_snh=55-lambda_inh=3.9-lambda_idf=10	0.884
vstan-k=1540-sample_size=5750-lambda_spw=0.92-lambda_snh=56-lambda_inh=1.5-lambda_idf=14	0.885
vstan-k=2000-sample_size=5650-lambda_spw=0.98-lambda_snh=52-lambda_inh=0.51-lambda_idf=5	0.887
vstan-k=1200-sample_size=5800-lambda_spw=0.92-lambda_snh=51-lambda_inh=3.9-lambda_idf=10	0.884
vstan-k=1550-sample_size=5800-lambda_spw=0.93-lambda_snh=500-lambda_inh=0.51-lambda_idf=8	0.880
vstan-k=1500-sample_size=5800-lambda_spw=0.98-lambda_snh=56-lambda_inh=1.8-lambda_idf=9	0.884
vstan-k=1400-sample_size=5550-lambda_spw=0.97-lambda_snh=59-lambda_inh=0.51-lambda_idf=1	0.887
vstan-k=1500-sample_size=5600-lambda_spw=0.91-lambda_snh=55-lambda_inh=3.9-lambda_idf=1	0.883
vstan-k=1500-sample_size=5500-lambda_spw=0.91-lambda_snh=450-lambda_inh=1.3-lambda_idf=15	0.878
vstan-k=1600-sample_size=5900-lambda_spw=0.101-lambda_snh=50-lambda_inh=3.9-lambda_idf=1	0.881
vstan-k=1000-sample_size=5900-lambda_spw=0.106-lambda_snh=300-lambda_inh=0.51-lambda_idf=11	0.877
vstan-k=1400-sample_size=5550-lambda_spw=0.91-lambda_snh=52-lambda_inh=1.5-lambda_idf=3	0.885
vstan-k=1600-sample_size=5650-lambda_spw=0.97-lambda_snh=350-lambda_inh=3.4-lambda_idf=5	0.879
vstan-k=2500-sample_size=6000-lambda_spw=0.95-lambda_snh=53-lambda_inh=2.4-lambda_idf=13	0.884
vstan-k=1600-sample_size=5500-lambda_spw=0.96-lambda_snh=400-lambda_inh=0.51-lambda_idf=11	0.881
vstan-k=1550-sample_size=5650-lambda_spw=0.96-lambda_snh=55-lambda_inh=2.4-lambda_idf=11	0.884
vstan-k=1600-sample_size=5800-lambda_spw=0.95-lambda_snh=350-lambda_inh=0.51-lambda_idf=6	0.881
vstan-k=2500-sample_size=5400-lambda_spw=0.99-lambda_snh=59-lambda_inh=1.5-lambda_idf=9	0.885
vstan-k=1530-sample_size=5750-lambda_spw=0.11-lambda_snh=59-lambda_inh=3.4-lambda_idf=3	0.880
vstan-k=1540-sample_size=5800-lambda_spw=0.104-lambda_snh=52-lambda_inh=1.5-lambda_idf=3	0.881
vstan-k=3000-sample_size=5550-lambda_spw=0.11-lambda_snh=500-lambda_inh=1.5-lambda_idf=13	0.878
vstan-k=1510-sample_size=5800-lambda_spw=0.105-lambda_snh=59-lambda_inh=3.8-lambda_idf=15	0.881
vstan-k=3000-sample_size=5600-lambda_spw=0.105-lambda_snh=60-lambda_inh=1.8-lambda_idf=10	0.880
vstan-k=1400-sample_size=5750-lambda_spw=0.106-lambda_snh=300-lambda_inh=3.8-lambda_idf=9	0.877
vstan-k=1550-sample_size=5900-lambda_spw=0.105-lambda_snh=300-lambda_inh=1.8-lambda_idf=14	0.876
vstan-k=1560-sample_size=5750-lambda_spw=0.96-lambda_snh=57-lambda_inh=0.51-lambda_idf=14	0.887
vstan-k=1540-sample_size=5650-lambda_spw=0.107-lambda_snh=500-lambda_inh=0.51-lambda_idf=8	0.879
vstan-k=1540-sample_size=5600-lambda_spw=0.104-lambda_snh=55-lambda_inh=1.8-lambda_idf=9	0.881
vstan-k=2500-sample_size=5600-lambda_spw=0.101-lambda_snh=500-lambda_inh=1.3-lambda_idf=6	0.875
vstan-k=2000-sample_size=5800-lambda_spw=0.107-lambda_snh=56-lambda_inh=2.4-lambda_idf=4	0.881
vstan-k=1200-sample_size=5800-lambda_spw=0.108-lambda_snh=52-lambda_inh=3.4-lambda_idf=12	0.881
vstan-k=1400-sample_size=5600-lambda_spw=0.106-lambda_snh=350-lambda_inh=3.9-lambda_idf=3	0.877
vstan-k=1200-sample_size=5400-lambda_spw=0.99-lambda_snh=350-lambda_inh=1.5-lambda_idf=14	0.877
vstan-k=1600-sample_size=5400-lambda_spw=0.92-lambda_snh=500-lambda_inh=1.8-lambda_idf=6	0.878
vstan-k=3000-sample_size=5550-lambda_spw=0.102-lambda_snh=300-lambda_inh=3.4-lambda_idf=13	0.878
vstan-k=3000-sample_size=5900-lambda_spw=0.97-lambda_snh=60-lambda_inh=1.3-lambda_idf=6	0.885
vstan-k=2500-sample_size=5800-lambda_spw=0.97-lambda_snh=54-lambda_inh=1.3-lambda_idf=9	0.885
vstan-k=1510-sample_size=6000-lambda_spw=0.94-lambda_snh=51-lambda_inh=3.4-lambda_idf=15	0.884
vstan-k=2000-sample_size=5500-lambda_spw=0.107-lambda_snh=200-lambda_inh=3.8-lambda_idf=12	0.878
vstan-k=1520-sample_size=5650-lambda_spw=0.109-lambda_snh=300-lambda_inh=3.8-lambda_idf=8	0.875
vstan-k=1530-sample_size=5400-lambda_spw=0.102-lambda_snh=500-lambda_inh=3.9-lambda_idf=12	0.875
vstan-k=1510-sample_size=5500-lambda_spw=0.93-lambda_snh=56-lambda_inh=1.5-lambda_idf=5	0.885
vstan-k=1540-sample_size=5650-lambda_spw=0.93-lambda_snh=60-lambda_inh=2.4-lambda_idf=5	0.884
vstan-k=1540-sample_size=5800-lambda_spw=0.108-lambda_snh=54-lambda_inh=2.4-lambda_idf=11	0.881
vstan-k=3000-sample_size=5600-lambda_spw=0.109-lambda_snh=500-lambda_inh=2.4-lambda_idf=10	0.878
vstan-k=1540-sample_size=5900-lambda_spw=0.93-lambda_snh=58-lambda_inh=1.5-lambda_idf=2	0.885
vstan-k=1510-sample_size=5750-lambda_spw=0.107-lambda_snh=54-lambda_inh=3.4-lambda_idf=11	0.881
vstan-k=1540-sample_size=5800-lambda_spw=0.93-lambda_snh=53-lambda_inh=1.3-lambda_idf=11	0.885
vstan-k=2000-sample_size=5750-lambda_spw=0.98-lambda_snh=51-lambda_inh=3.4-lambda_idf=8	0.884
vstan-k=1550-sample_size=5500-lambda_spw=0.104-lambda_snh=50-lambda_inh=1.5-lambda_idf=13	0.882
vstan-k=150-sample_size=190-lambda_spw=11.206-lambda_snh=5-lambda_inh=3.12-lambda_idf=1	0.907

Hyperparameters for SFSKNN

We tested the following hyperparameter space:

Parameter	Options
Number of Neighbors	[50, 100, 500, 600, 700, 800, 1000, 1300, 1400, 1500, 1700, 2000, 2500, 2800, 3000]
Sample Size	[500, 600, 1000, 1100, 2500, 1900, 5000, 7000, 8000, 10000]
Similarity	[tanimoto, binary, cosine]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.369
• Standard deviation: 0.003
• Maximum value: 0.371
• Minimum value: 0.361

Parameters/Metrics	MRR@20
sfsknn-k=50-sample_size=1000-similarity=tanimoto	0.363
sfsknn-k=100-sample_size=5000-similarity=tanimoto	0.366
sfsknn-k=50-sample_size=2000-similarity=binary	0.361
sfsknn-k=1000-sample_size=1500-similarity=cosine	0.371
sfsknn-k=800-sample_size=1500-similarity=cosine	0.371
sfsknn-k=1000-sample_size=10000-similarity=binary	0.368
sfsknn-k=2500-sample_size=2500-similarity=tanimoto	0.371
sfsknn-k=50-sample_size=5000-similarity=cosine	0.365
sfsknn-k=2000-sample_size=5000-similarity=tanimoto	0.371
sfsknn-k=2000-sample_size=1000-similarity=tanimoto	0.371
sfsknn-k=2000-sample_size=2000-similarity=tanimoto	0.371
sfsknn-k=800-sample_size=10000-similarity=tanimoto	0.370
sfsknn-k=2000-sample_size=5000-similarity=cosine	0.371
sfsknn-k=500-sample_size=1500-similarity=cosine	0.371
sfsknn-k=1500-sample_size=5000-similarity=binary	0.369
sfsknn-k=100-sample_size=1500-similarity=tanimoto	0.366
sfsknn-k=2500-sample_size=500-similarity=cosine	0.371
sfsknn-k=1500-sample_size=5000-similarity=tanimoto	0.371
sfsknn-k=2000-sample_size=2500-similarity=cosine	0.371
sfsknn-k=1500-sample_size=500-similarity=cosine	0.371
sfsknn-k=500-sample_size=500-similarity=binary	0.369
sfsknn-k=800-sample_size=10000-similarity=cosine	0.371
sfsknn-k=500-sample_size=1000-similarity=tanimoto	0.370
sfsknn-k=800-sample_size=2000-similarity=cosine	0.371
sfsknn-k=1000-sample_size=10000-similarity=cosine	0.371
sfsknn-k=2000-sample_size=10000-similarity=tanimoto	0.371
sfsknn-k=2500-sample_size=10000-similarity=binary	0.369
sfsknn-k=100-sample_size=500-similarity=cosine	0.371
sfsknn-k=2500-sample_size=2000-similarity=binary	0.369
sfsknn-k=500-sample_size=2000-similarity=binary	0.369
sfsknn-k=100-sample_size=5000-similarity=cosine	0.369
sfsknn-k=800-sample_size=1000-similarity=binary	0.369
sfsknn-k=1500-sample_size=10000-similarity=tanimoto	0.371
sfsknn-k=1000-sample_size=2500-similarity=binary	0.368
sfsknn-k=2000-sample_size=1500-similarity=binary	0.369
sfsknn-k=2000-sample_size=1500-similarity=cosine	0.371
sfsknn-k=800-sample_size=2000-similarity=tanimoto	0.370
sfsknn-k=50-sample_size=2500-similarity=binary	0.361
sfsknn-k=800-sample_size=1000-similarity=cosine	0.371
sfsknn-k=100-sample_size=2500-similarity=tanimoto	0.366
sfsknn-k=1500-sample_size=2500-similarity=tanimoto	0.371
sfsknn-k=100-sample_size=2000-similarity=tanimoto	0.366
sfsknn-k=2500-sample_size=500-similarity=binary	0.369
sfsknn-k=2500-sample_size=1500-similarity=binary	0.369
sfsknn-k=2500-sample_size=5000-similarity=tanimoto	0.371
sfsknn-k=800-sample_size=5000-similarity=cosine	0.371
sfsknn-k=1000-sample_size=1000-similarity=cosine	0.371
sfsknn-k=50-sample_size=1500-similarity=tanimoto	0.363
sfsknn-k=100-sample_size=5000-similarity=binary	0.364
sfsknn-k=500-sample_size=1000-similarity=binary	0.368
sfsknn-k=2500-sample_size=2000-similarity=cosine	0.371
sfsknn-k=500-sample_size=2500-similarity=cosine	0.371
sfsknn-k=800-sample_size=500-similarity=tanimoto	0.371
sfsknn-k=1000-sample_size=1500-similarity=binary	0.368
sfsknn-k=500-sample_size=1500-similarity=tanimoto	0.370
sfsknn-k=1000-sample_size=2000-similarity=tanimoto	0.370
sfsknn-k=2000-sample_size=500-similarity=binary	0.369
sfsknn-k=50-sample_size=500-similarity=tanimoto	0.364
sfsknn-k=500-sample_size=10000-similarity=binary	0.369
sfsknn-k=500-sample_size=2500-similarity=tanimoto	0.370
sfsknn-k=100-sample_size=1000-similarity=tanimoto	0.366
sfsknn-k=1000-sample_size=1000-similarity=binary	0.369
sfsknn-k=800-sample_size=500-similarity=binary	0.369
sfsknn-k=50-sample_size=1500-similarity=cosine	0.365
sfsknn-k=500-sample_size=5000-similarity=tanimoto	0.370
sfsknn-k=800-sample_size=2000-similarity=binary	0.369
sfsknn-k=500-sample_size=2000-similarity=tanimoto	0.370
sfsknn-k=100-sample_size=500-similarity=tanimoto	0.367
sfsknn-k=1000-sample_size=1000-similarity=tanimoto	0.371
sfsknn-k=500-sample_size=10000-similarity=cosine	0.371
sfsknn-k=2000-sample_size=2500-similarity=binary	0.369
sfsknn-k=2000-sample_size=10000-similarity=binary	0.369
sfsknn-k=2000-sample_size=1000-similarity=cosine	0.371
sfsknn-k=50-sample_size=1000-similarity=binary	0.361
sfsknn-k=2000-sample_size=1500-similarity=tanimoto	0.371
sfsknn-k=500-sample_size=10000-similarity=tanimoto	0.370

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.239
• Standard deviation: 0.002
• Maximum value: 0.242
• Minimum value: 0.236

Parameters/Metrics	MRR@20
sfsknn-k=50-sample_size=5000-similarity=tanimoto	0.237
sfsknn-k=1000-sample_size=2500-similarity=tanimoto	0.240
sfsknn-k=500-sample_size=1000-similarity=tanimoto	0.240
sfsknn-k=1500-sample_size=2000-similarity=tanimoto	0.240
sfsknn-k=500-sample_size=5000-similarity=binary	0.239
sfsknn-k=1000-sample_size=10000-similarity=binary	0.239
sfsknn-k=1500-sample_size=2500-similarity=tanimoto	0.240
sfsknn-k=1500-sample_size=1000-similarity=tanimoto	0.240
sfsknn-k=50-sample_size=5000-similarity=cosine	0.239
sfsknn-k=500-sample_size=10000-similarity=tanimoto	0.240
sfsknn-k=50-sample_size=10000-similarity=tanimoto	0.237
sfsknn-k=2000-sample_size=1500-similarity=tanimoto	0.240
sfsknn-k=50-sample_size=5000-similarity=binary	0.236
sfsknn-k=1000-sample_size=2000-similarity=cosine	0.242
sfsknn-k=500-sample_size=5000-similarity=cosine	0.242
sfsknn-k=2000-sample_size=500-similarity=tanimoto	0.240
sfsknn-k=1000-sample_size=500-similarity=binary	0.239
sfsknn-k=50-sample_size=1500-similarity=cosine	0.239
sfsknn-k=2000-sample_size=1000-similarity=cosine	0.242
sfsknn-k=1000-sample_size=1500-similarity=tanimoto	0.240
sfsknn-k=500-sample_size=2000-similarity=cosine	0.242
sfsknn-k=1000-sample_size=5000-similarity=cosine	0.242
sfsknn-k=1000-sample_size=5000-similarity=binary	0.239
sfsknn-k=1000-sample_size=10000-similarity=cosine	0.242
sfsknn-k=1000-sample_size=2500-similarity=cosine	0.242
sfsknn-k=50-sample_size=2000-similarity=cosine	0.239
sfsknn-k=500-sample_size=2000-similarity=binary	0.239
sfsknn-k=100-sample_size=5000-similarity=cosine	0.239
sfsknn-k=2000-sample_size=1000-similarity=binary	0.239
sfsknn-k=100-sample_size=2500-similarity=tanimoto	0.240
sfsknn-k=1500-sample_size=2500-similarity=binary	0.239
sfsknn-k=1500-sample_size=10000-similarity=binary	0.239
sfsknn-k=2000-sample_size=2500-similarity=tanimoto	0.240
sfsknn-k=50-sample_size=1000-similarity=binary	0.236
sfsknn-k=500-sample_size=5000-similarity=tanimoto	0.240
sfsknn-k=2000-sample_size=500-similarity=cosine	0.242
sfsknn-k=2000-sample_size=5000-similarity=tanimoto	0.240
sfsknn-k=1500-sample_size=10000-similarity=tanimoto	0.240
sfsknn-k=100-sample_size=1500-similarity=tanimoto	0.240
sfsknn-k=1500-sample_size=1500-similarity=cosine	0.242
sfsknn-k=2000-sample_size=1500-similarity=cosine	0.242
sfsknn-k=500-sample_size=2000-similarity=tanimoto	0.240
sfsknn-k=1000-sample_size=2000-similarity=binary	0.239
sfsknn-k=50-sample_size=2000-similarity=binary	0.236
sfsknn-k=1000-sample_size=1500-similarity=binary	0.239
sfsknn-k=1500-sample_size=500-similarity=tanimoto	0.240
sfsknn-k=1500-sample_size=2000-similarity=cosine	0.242
sfsknn-k=50-sample_size=2500-similarity=cosine	0.239
sfsknn-k=500-sample_size=500-similarity=binary	0.239
sfsknn-k=50-sample_size=2500-similarity=tanimoto	0.237
sfsknn-k=50-sample_size=1000-similarity=cosine	0.239
sfsknn-k=50-sample_size=10000-similarity=binary	0.236
sfsknn-k=100-sample_size=1000-similarity=cosine	0.239
sfsknn-k=50-sample_size=500-similarity=cosine	0.239
sfsknn-k=500-sample_size=2500-similarity=cosine	0.242
sfsknn-k=1000-sample_size=500-similarity=cosine	0.242
sfsknn-k=1500-sample_size=1000-similarity=binary	0.239
sfsknn-k=500-sample_size=1000-similarity=binary	0.239
sfsknn-k=50-sample_size=500-similarity=binary	0.236
sfsknn-k=500-sample_size=1500-similarity=binary	0.239
sfsknn-k=100-sample_size=2000-similarity=cosine	0.239
sfsknn-k=2000-sample_size=10000-similarity=binary	0.239
sfsknn-k=2000-sample_size=1000-similarity=tanimoto	0.240
sfsknn-k=100-sample_size=2500-similarity=binary	0.241

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.591
• Standard deviation: 0.005
• Maximum value: 0.604
• Minimum value: 0.588

Parameters/Metrics	MRR@20
sfsknn-k=200-sample_size=500	0.589
sfsknn-k=150-sample_size=800	0.588
sfsknn-k=20-sample_size=300	0.604
sfsknn-k=30-sample_size=800	0.602
sfsknn-k=50-sample_size=1000	0.591
sfsknn-k=50-sample_size=500	0.591
sfsknn-k=200-sample_size=800	0.588
sfsknn-k=50-sample_size=300	0.590
sfsknn-k=200-sample_size=600	0.589
sfsknn-k=150-sample_size=600	0.588
sfsknn-k=150-sample_size=1000	0.588
sfsknn-k=150-sample_size=500	0.588
sfsknn-k=100-sample_size=1000	0.590

Hyperparameters for SR

We tested the following hyperparameter space:

Parameter	Ranges
Steps	[1 to 20]
Weighting	[log, quadratic, linear, same]

Tuning on DIGI dataset

Statistical values based on MRR@20

• Average: 0.310
• Standard deviation: 0.019
• Maximum value: 0.334
• Minimum value: 0.279

Parameters/Metrics	MRR@20
sr-steps=20-weighting=log	0.297
sr-steps=2-weighting=quadratic	0.332
sr-steps=18-weighting=log	0.297
sr-steps=2-weighting=linear	0.324
sr-steps=3-weighting=linear	0.310
sr-steps=15-weighting=log	0.298
sr-steps=10-weighting=linear	0.298
sr-steps=3-weighting=same	0.306
sr-steps=10-weighting=log	0.298
sr-steps=12-weighting=div	0.325
sr-steps=10-weighting=same	0.281
sr-steps=10-weighting=div	0.325
sr-steps=15-weighting=same	0.282
sr-steps=3-weighting=quadratic	0.331
sr-steps=15-weighting=quadratic	0.334
sr-steps=5-weighting=log	0.298
sr-steps=5-weighting=div	0.331
sr-steps=3-weighting=div	0.331
sr-steps=12-weighting=same	0.279
sr-steps=12-weighting=quadratic	0.334
sr-steps=15-weighting=linear	0.300
sr-steps=2-weighting=div	0.330
sr-steps=12-weighting=log	0.297
sr-steps=10-weighting=quadratic	0.334
sr-steps=3-weighting=log	0.313
sr-steps=20-weighting=quadratic	0.334
sr-steps=12-weighting=linear	0.299
sr-steps=18-weighting=linear	0.299
sr-steps=18-weighting=same	0.279
sr-steps=20-weighting=div	0.325
sr-steps=15-weighting=div	0.325
sr-steps=2-weighting=log	0.324
sr-steps=5-weighting=linear	0.299
sr-steps=20-weighting=linear	0.299
sr-steps=20-weighting=same	0.279
sr-steps=5-weighting=same	0.291

Tuning on RSC15 dataset

Statistical values based on MRR@20

• Average: 0.229
• Standard deviation: 0.004
• Maximum value: 0.234
• Minimum value: 0.220

Parameters/Metrics	MRR@20
sr-steps=20-weighting=div	0.228
sr-steps=5-weighting=div	0.231
sr-steps=12-weighting=log	0.231
sr-steps=18-weighting=div	0.228
sr-steps=3-weighting=log	0.233
sr-steps=15-weighting=same	0.222
sr-steps=3-weighting=quadratic	0.231
sr-steps=18-weighting=same	0.221
sr-steps=18-weighting=log	0.230
sr-steps=5-weighting=linear	0.234
sr-steps=12-weighting=quadratic	0.225
sr-steps=20-weighting=same	0.220
sr-steps=2-weighting=quadratic	0.229
sr-steps=20-weighting=quadratic	0.225
sr-steps=12-weighting=same	0.223
sr-steps=10-weighting=log	0.230
sr-steps=3-weighting=div	0.231
sr-steps=3-weighting=linear	0.232
sr-steps=12-weighting=div	0.228
sr-steps=10-weighting=div	0.228
sr-steps=3-weighting=same	0.220
sr-steps=15-weighting=log	0.229
sr-steps=10-weighting=same	0.225
sr-steps=15-weighting=linear	0.233
sr-steps=12-weighting=linear	0.233
sr-steps=15-weighting=div	0.228
sr-steps=2-weighting=div	0.228
sr-steps=18-weighting=quadratic	0.225
sr-steps=5-weighting=quadratic	0.228
sr-steps=18-weighting=linear	0.232
sr-steps=10-weighting=linear	0.233
sr-steps=2-weighting=log	0.231
sr-steps=20-weighting=linear	0.232
sr-steps=5-weighting=log	0.234
sr-steps=10-weighting=quadratic	0.224

Tuning on RETAIL dataset

Statistical values based on MRR@20

• Average: 0.538
• Standard deviation: 0.014
• Maximum value: 0.554
• Minimum value: 0.510

Parameters/Metrics	MRR@20
sr-steps=20-weighting=linear	0.530
sr-steps=5-weighting=same	0.519
sr-steps=15-weighting=div	0.550
sr-steps=2-weighting=div	0.547
sr-steps=3-weighting=same	0.530
sr-steps=3-weighting=div	0.554
sr-steps=20-weighting=log	0.534
sr-steps=12-weighting=linear	0.530
sr-steps=3-weighting=log	0.551
sr-steps=20-weighting=div	0.550
sr-steps=12-weighting=same	0.511
sr-steps=10-weighting=div	0.548
sr-steps=2-weighting=linear	0.538
sr-steps=10-weighting=log	0.534
sr-steps=18-weighting=quadratic	0.550
sr-steps=5-weighting=quadratic	0.553
sr-steps=18-weighting=div	0.550
sr-steps=18-weighting=log	0.534
sr-steps=5-weighting=linear	0.544
sr-steps=3-weighting=linear	0.551
sr-steps=10-weighting=quadratic	0.548
sr-steps=5-weighting=log	0.545
sr-steps=12-weighting=quadratic	0.550
sr-steps=15-weighting=same	0.511
sr-steps=18-weighting=same	0.511
sr-steps=20-weighting=same	0.511
sr-steps=12-weighting=log	0.534
sr-steps=2-weighting=quadratic	0.543
sr-steps=15-weighting=quadratic	0.550
sr-steps=5-weighting=div	0.552
sr-steps=10-weighting=same	0.510
sr-steps=3-weighting=quadratic	0.549
sr-steps=15-weighting=linear	0.530
sr-steps=10-weighting=linear	0.530
sr-steps=15-weighting=log	0.534
sr-steps=20-weighting=quadratic	0.550
sr-steps=18-weighting=linear	0.530