Jointly Modelling Aspects, Ratings and Sentiments for Movie Recommendation (JMARS)
http://www.andrew.cmu.edu/user/chaoyuaw/jmars_kdd2014.pdf
To run the code, download the data file from the following link:
https://www.dropbox.com/s/0oea49j7j30y671/data.json?dl=0
and store in a folder named 'data'
Then run jmars.py as a python file:
python jmars.py
File Descriptions:
constants.py - Contains constants and global variables
indexer.py - Contains code to read imdb data and extract relevant information
optimize.py - Contains code to run optimization needed in the M-Step
sampler.py - Contains code to run Gibbs Sampling needed in the E-Step
jmars.py - Contains main code which uses the other modules and runs Gibbs Expectation-Maximization to output predicted ratings
Github Link: https://github.com/nihalb/JMARS