Data augmentation method for session-based recommendation
item :
FA = Frequency of appearance
HS = Highest similarity value
by running preprocessing.py, following folder hierarchy is made.
da_for_sbr(main folder)
|-main.ipynb
|-preprocessing.py
|-simmetric.py
|-utils.py
|-narm_torch
|-srgnn_torch
|-exps
| |-experiment1
| | |-yoochoose (train files, test files)
| | |-diginetica (train files, test files)
| | |-result_narm_yoochoose
| | | |-y064
| | | |-y128
| | | |-y256
| | | |-y512
| | |-result_narm_diginetica
| | | |-d001
| | | |-d003
| | | |-d006
| | | |-d012
| | |-result_srgnn_yoochoose
| | | |-y064
| | | |-y128
| | | |-y256
| | | |-y512
| | |-result_srgnn_diginetica
| | | |-d001
| | | |-d003
| | | |-d006
| | | |-d012
| |-experiment(n)
| |-train_item_views.csv
| |-yoochoose-clicks-withHeader.dat\
-train_item_views.csv (https://drive.google.com/file/d/14_Gej2IzMyIR6bVQ0O7mR34Ln20NYt4v/view?usp=sharing)
-yoochoose-clicks-withHeader.dat (https://drive.google.com/file/d/14YJ6Pntx3a2b9If9DgzF9Ax2Po9SUk_W/view?usp=sharing)