Book-Crossing.md

Experimental setting

Source domain dataset: Book-Crossing

Target domain dataset: Librarything

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"
item_link_file_path: ./datasets/Book-Crossing_Librarything.link
source_domain:
  dataset: Book-Crossing
  USER_ID_FIELD: user_id
  ITEM_ID_FIELD: ISBN
  RATING_FIELD: rating
  TIME_FIELD: timestamp
  NEG_PREFIX: neg_
  LABEL_FIELD: label
  load_col:
    inter: [user_id, ISBN, rating]
  user_inter_num_interval: "[5,inf)"
  item_inter_num_interval: "[0,inf)"
  val_interval:
    rating: "[5,inf)"
  drop_filter_field: True

target_domain:
  dataset: Librarything
  USER_ID_FIELD: user_id
  ITEM_ID_FIELD: book_name
  RATING_FIELD: rating
  TIME_FIELD: timestamp
  NEG_PREFIX: neg_
  LABEL_FIELD: label
  load_col:
    inter: [user_id, book_name, rating]
  user_inter_num_interval: "[5,inf)"
  item_inter_num_interval: "[5,inf)"
  val_interval:
    rating: "[5,inf)"
  drop_filter_field: True
# training and evaluation
epochs: 500
train_batch_size: 4096
eval_batch_size: 4096000
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 Statistics

Dataset	#Users	#items	#Interactions	Sparsity
Book-Crossing	13581	153430	324049	99.98%
Librarything	6783	9502	379908	99.31%

Number of Overlapped User: 0

Number of Overlapped Item: 2799

Hyper-parameters

Method	Best hyper-parameters
CoNet	learning_rate=0.005 mlp_hidden_size=[64,32,16,8] reg_weight=0.01
CLFM	learning_rate=0.0005 share_embedding_size=32 alpha=0.5 reg_weight=0.001
DTCDR	learning_rate=0.0005 mlp_hidden_size=[64,64] dropout_prob=0.3 alpha=0.3 base_model=NeuMF
DeepAPF	learning_rate=0.001
BiTGCF	learning_rate=0.0005 n_layers=2 concat_way=concat lambda_source=0.8 lambda_target=0.8 drop_rate=0.1 reg_weight=0.001
CMF	learning_rate=0.0005 lambda=0.7 gamma=0.1 alpha=0.3
EMCDR	learning_rate=0.001 mapping_function=linear mlp_hidden_size=[32] overlap_batch_size=300 reg_weight=0.001 latent_factor_model=BPR loss_type=BPR
NATR	learning_rate=0.005 max_inter_length=100 reg_weight=1e-5
SSCDR	learning_rate=0.0005 lambda=0 margin=0.2 overlap_batch_size=1024
DCDCSR	learning_rate=0.0005 mlp_hidden_size=[128] k=10