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generative-adversarial-user-model-for-reinforcement-learning-based-recommendation-system-pytorch's Introduction

Generative-Adversarial-User-Model-for-Reinforcement-Learning-Based-Recommendation-System-Pytorch

Pytorch implementation of Recommendation System based on Generative Adverserial Reinforcement Learning based user Model Implementation of the paper under same title paper

This Repo Include:

  1. Data Necessary (Yelp Reviews)
  2. Data Preprocessing
  3. Position Weigth (PW) Model
  4. Hyperparameter Tuned Model

To Train:

Simply Run reco_gan_rl jupyter notebook. It includes both preprocessing of the data as well as training

To DO:

  1. Add LSTM Model

Note:

The data processing is mainly based on original implementation so that the results could be compared .Source

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generative-adversarial-user-model-for-reinforcement-learning-based-recommendation-system-pytorch's Issues

about source dataset yelp.txt

hello, how can I get the dataset "yelp.txt" you use in the experiment? Can you upload it too?
=>preprocess_data.py / filename = opts.data_folder+opts.dataset+'.txt'

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