Source domain dataset: Amazon-Books
Target domain dataset: Amazon-Movie
Evaluation: all users in target dataset, ratio-based 8:1:1, full sort
Metrics: Recall, Precision, NDCG, MRR, Hit
Topk: 10, 20, 50
Properties:
seed: 2022
field_separator: "\t"
source_domain:
dataset: AmazonBooks
USER_ID_FIELD: user_id
ITEM_ID_FIELD: item_id
RATING_FIELD: rating
TIME_FIELD: timestamp
NEG_PREFIX: neg_
LABEL_FIELD: label
load_col:
inter: [user_id, item_id, rating]
user_inter_num_interval: "[10,inf)"
item_inter_num_interval: "[10,inf)"
val_interval:
rating: "[3,inf)"
drop_filter_field: True
target_domain:
dataset: AmazonMov
USER_ID_FIELD: user_id
ITEM_ID_FIELD: item_id
RATING_FIELD: rating
TIME_FIELD: timestamp
NEG_PREFIX: neg_
LABEL_FIELD: label
load_col:
inter: [user_id, item_id, rating]
user_inter_num_interval: "[10,inf)"
item_inter_num_interval: "[10,inf)"
val_interval:
rating: "[3,inf)"
drop_filter_field: True
epochs: 500
train_batch_size: 4096
eval_batch_size: 409600
valid_metric: NDCG@10
For fairness, we restrict users' and items' embedding dimension as following. Please adjust the name of the corresponding args of different models.
embedding_size: 64
Dataset | #Users | #items | #Interactions | Sparsity |
---|---|---|---|---|
Amazon-Books | 135109 | 115172 | 4042382 | 99.97% |
Amazon-Movie | 26968 | 18563 | 762957 | 99.85% |
Number of Overlapped User: 5982
Number of Overlapped Item: 0
Method | Best hyper-parameters |
---|---|
CoNet | learning_rate=0.005 mlp_hidden_size=[32,32,16,8] reg_weight=0.001 |
CLFM | learning_rate=0.0005 share_embedding_size=32 alpha=0.1 reg_weight=0.0001 |
DTCDR | learning_rate=0.0005 mlp_hidden_size=[64,64] dropout_prob=0.3 alpha=0.3 base_model=NeuMF |
DeepAPF | learning_rate=0.00001 |
BiTGCF | learning_rate=0.0001 n_layers=3 concat_way=mean lambda_source=0.8 lambda_target=0.8 drop_rate=0.1 reg_weight=0.01 |
CMF | learning_rate=0.0005 lambda=0.2 gamma=0.1 alpha=0.2 |
EMCDR | learning_rate=0.001 mapping_function=non_linear mlp_hidden_size=[128] overlap_batch_size=300 reg_weight=0.01 latent_factor_model=BPR loss_type=BPR |
NATR | learning_rate=0.001 max_inter_length=100 reg_weight=1e-5 |
SSCDR | learning_rate=0.0005 lambda=0.05 margin=0.3 overlap_batch_size=1024 |
DCDCSR | learning_rate=0.0005 mlp_hidden_size=[128] k=10 |