1) The data for Distinguishing Feature(DF) model is generated using pairwise_comparisonsC.py, data for BTL model is generated using Data_BTL_model.py, data for Salient Features(SF) model 
is generated using SFmodel_Data.py.

- The embeddings for the items are generated using gen_embedding.py in both DF and SF model.
- The weights in SF models are generated using SF_model_weights.py.
- Scores for BTL model are generated using Generate_Score_BTL.py.


2) Run RC_SF_DFlearn_DFdata.py for all the 3 algorithms on data generated from Distinguishing Feature model.
3) Run RC_SF_DFlearn_BTLdata.py for all the 3 algorithms on data generated from BTL model.
4) Run RC_SF_DFlearn_SFdata.py for all the 3 algorithms on data generated from Salient Features model.

5) DFlearn.py contains the code for DFLearn algorithm, RC.py contains the code for Rank Centrality, SFmodel_MLE.py contains the code for MLE implemented for SF model.

6) DOTA, HotS_Starcraft, jester, movielens_100k, WoL_Starcraft are the 5 real world datasets used.
7) Run Dota_RC_SF_DF.py for DOTA.csv and jester.csv for all 3 algorithms given above.
8) Run HotS_WoL_movielens.py for other 3 datasets.


