The file write_up.pdf explains the methodology behind training and what features were extracted for each classifier task

The following files are the part of the project

ARFF FILES

1. starRatingSameUsersTrain.arff
2. starRatingDiffUsersTrain.arff
3. binaryRatingSameUsersTrain.arff
4. binaryRatingDiffUsersTrain.arff
5. authorTrain.arff

SCRIPT FILES

1. author.sh
2. starRatingSameUsers.sh
3. starRatingDiffUsers.sh
4. binaryRatingSameUsers.sh
5. binaryRatingDiffUsers.sh

################################################################################################################## SCRIPT FILE USAGE

$ ./script_file_name.sh model_name.model movie-review-file.txt labelled-output-reviews.txt ##################################################################################################################

MODEL FILES

1. author.model - generated using SVM classifier
2. binaryRatingSameUsers.model - generated using NB classifier
3. binaryRatingDiffUSers.model - same as binaryRatingSameUsers.model
4. starRatingSameUsers.model - generated using SVM classifier
5. starRatingDiffUsers.model - same as starRatingSameUsers.model

The models were made as generalized as possible without using any domain specific information. Hence the same were specified in both the same users and in the different users case.

FEATURE EXTRACTING FEATURE FILES

1. quart_score.py - Extracts features for the 4 star classification task
2. binary4.py - Extracts features for the 2 class Positive-Negative Classification
3. author1.py - Extracts features for the Reviewer Classification Task

############################################################################################### PYTHON FILE USAGE

$ python python_file.py movie-review-file.txt feature-file.arff ###############################################################################################

SUPPORTING PYTHON FILES -- prepare the final output text document with the predicted output inserted into the text document

1. final_star.py
2. final_binary.py
3. final.py

Also attached is SentiWordNet which is located in the file senti.txt