NNCF
Implementation of Neighborhood-based Neural Collaborative Filtering model (NNCF)
Ting Bai et al. "A Neural Collaborative Filtering Model with Interaction-based Neighborhood." Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. ACM, 2017.
==========Run the model: python main.py===========
Take Rossmann for example
Parameters:
N_test_negative(99): the number of negative samples in the testing ranking list
max_neighbors(50): the maximum neighbors in our algorithm
N_train_negative(4): the number of negative samples in training
embedding_dim(32): the output dimension of MLP
nb_layer(3): the number of layers in MLP
nb_epoch(100): training epoch
LR(0.001): learning rate
================================File Description===========================
01: Process input data: data.csv (userid,itemid)
02: Split train & test set and construct graph
03,04: Construct direct neighbors of model (NNCF_direct)
03-1,04-1: Construct community neighbors of model (NNCF_community)
03-2: Construct knn neighbors of model (NNCF_knn)
05: Training model
06: Evaluation of model
Python version: 2.7.3, Keras version：2.1.5, Tensorflow: 1.6.0.
Note: the python files are independent to make our project more flexible and extensible. You can tuning parameters and run the corresponding python file that you need.