Welcome to the Diagnosing Bias in Recommender Systems - Elliot repository! In this project, we experiment with detecting bias in recommender systems, using the framework Elliot, and testing the DMF algorithm. By following the steps below, you can set up the environment and run the provided Jupyter notebooks to conduct popularity bias analysis.
To get started with the Elliot project, follow the instructions below.
Make sure you have the following software installed:
- Python 3.8
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Create and activate a conda virtual environment:
conda create --name elliotenv python=3.8 conda activate elliotenv
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Clone the repository:
git clone https://github.com/SavvinaDaniil/Elliot.git cd Elliot -
Install the required Python packages:
pip install -r requirements.txt
Once you have completed the installation steps, you can now run the bias analysis experiment using the provided Jupyter notebook.
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Start the Jupyter notebook server:
jupyter notebook
Make sure that jupyter points to the jupyter installed from the requirements file. You may need to deactivate and activate the environment again.
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Open the notebooks from the project directory. Each notebook performs a different process by calling the appropriate widget. You can select which dataset you wish to perform the process on.