spmf-mnar

This is our source code for the paper:
Jiawei Chen, Can Wang, Martin Ester, Qihao Shi, Yan Feng, and Chun Chen. Social Recommendation with Missing Not at Random Data. 2018 IEEE 18th International Conference on data mining.

Example to run the code.

We implement the SPMF-MNAR in MATLAB. Also, we implement some important function in C++ to speed up inference. So, beforing running the code, please compile c++ source codes to generate mex file in matlab enviornment:

mex myv2c.cpp
mex myv2s.cpp

Then, we can run the code for the exampledata:

spmfmnar('exampledata/train.txt','exampledata/test.txt','exampledata/trustnetwork.txt')

Where the inputs of the spmfmnar function are the paths of the trainning data, the test data and the trustnetwork respectively.
Each line of train.txt is: UserID \t ItemID \t ratingvalue
Each line of test.txt is :UserID \t ItemID \t ratingvalue
Each line of trustnetwork.txt is: User1ID \t User2ID \t strength(1)

jiawei-chen/spmf-mnar

spmf-mnar

Example to run the code.