sunshinelium/convmf_v2.0

This repository contains a modified version of ConvMF which is very interesting in RS.

ConvMF_V2.0

This is an updation of ConvMF

Because of that keras has updated from 1.0 to 2.0, So I update the core code in ConvMF. You can use the run_test.sh to test code in your environment after you download the code.

How to Run

Note: Run python <install_path>/run.py -h in bash shell. You will see how to configure several parameters for ConvMF

Configuration

You can evaluate our model with different settings in terms of the size of dimension, the value of hyperparameter, the number of convolutional kernal, and etc. Below is a description of all the configurable parameters and their defaults:

Parameter	Default
-h, --help	{}
-c <bool>, --do_preprocess <bool>	False
-r <path>, --raw_rating_data_path <path>	{}
-i <path>, --raw_item_document_data_path <path>	{}
-b <path>, --raw_user_side_information_data_path <path>	{}
-m <integer>, --min_rating <integer>	{}
-l <integer>, --max_length_document <integer>	300
-f <float>, --max_df <float>	0.5
-s <integer>, --vocab_size <integer>	8000
-t <float>, --split_ratio <float>	0.2
-d <path>, --data_path <path>	{}
-a <path>, --aux_path <path>	{}
-o <path>, --res_dir <path>	{}
-e <integer>, --emb_dim <integer>	200
-p <path>, --pretrain_w2v <path>	{}
-g <bool>, --give_item_weight <bool>	True
-k <integer>, --dimension <integer>	50
-u <float>, --lambda_u <float>	{}
-v <float>, --lambda_v <float>	{}
-n <integer>, --max_iter <integer>	200
-w <integer>, --num_kernel_per_ws	100

1. do_preprocess: True or False in order to preprocess raw data for ConvMF.
2. raw_rating_data_path: path to a raw rating data path. The data format should be user id::item id::rating.
3. min_rating: users who have less than min_rating ratings will be removed.
4. max_length_document: the maximum length of document of each item.
5. max_df: threshold to ignore terms that have a document frequency higher than the given value. i.e. for removing corpus-stop words.
6. vocab_size: size of vocabulary.
7. split_ratio: 1-ratio, ratio/2 and ratio/2 of the entire dataset will be constructed as training, valid and test set, respectively.
8. data_path: path to training, valid and test datasets.
9. aux_path: path to R, D_all sets that are generated during the preprocessing step.
10. res_dir: path to ConvMF's result
11. emb_dim: the size of latent dimension for word vectors.
12. pretrain_w2v: path to pretrained word embedding model to initialize word vectors.
13. give_item_weight : True or False to give item weight for R-ConvMF.
14. dimension: the size of latent dimension for users and items.
15. lambda_u: parameter of user regularizer.
16. lambda_v: parameter of item regularizer.
17. max_iter: the maximum number of iteration.
18. num_kernel_per_ws: the number of kernels per window size for CNN module.
19. raw_user_side_information_data_path path to a raw user side information path. the data format should be user id:: binaryvector
20. raw_item_document_data_path path to a raw item side information path. the data format should be item id:: review1 | review2 | review3 ...

If you have any question, don't hestitate to contact with me.

Email:[email protected]