code for the paper "Personalized Re-ranking for E-commerce Recommendation Systems"

rec_train_set.sample.data 8000 lines

rec_validation_set.sample.data 1000 lines

rec_test_set.sample.data 1000 lines

python main.py --train true --train_set dataset/rec_train_set.sample.txt --validation_set dataset/rec_validation_set.sample.txt --model_type 0 --batch_size 128 --train_epochs 10 --train_steps_per_epoch 10 --validation_steps 15 --early_stop_patience 3 --lr_per_step 1000 --saved_model_name drr_model_0.h5

python main.py --train true --train_set dataset/rec_train_set.sample.txt --validation_set dataset/rec_validation_set.sample.txt --model_type 1 --batch_size 128 --train_epochs 10 --train_steps_per_epoch 10 --validation_steps 15 --early_stop_patience 3 --lr_per_step 1000 --saved_model_name drr_model_1.h5

python main.py --train true --train_set dataset/rec_train_set.sample.txt --validation_set dataset/rec_validation_set.sample.txt --model_type 2 --batch_size 128 --train_epochs 10 --train_steps_per_epoch 10 --validation_steps 15 --early_stop_patience 3 --lr_per_step 1000 --d_feature 19 --saved_model_name drr_model_2.h5

python main.py --test_set dataset/rec_test_set.sample.txt --batch_size 2 --model_type 0 --saved_model_name drr_model_0.h5

python main.py --test_set dataset/rec_test_set.sample.txt --batch_size 2 --model_type 1 --saved_model_name drr_model_1.h5

python main.py --test_set dataset/rec_test_set.sample.txt --batch_size 2 --model_type 2 --saved_model_name drr_model_2.h5 --d_feature 19

python metric.py dataset/rec_test_set.sample.txt.predict.out