This repository contains the code to generate the datasets used in the AlignMacrid VAE model presented at ECIR 2024 in this paper. The resulting dataset is published in Kaggle in https://www.kaggle.com/datasets/ignacioavas/alignmacrid-vae.
This code was tested in Python 3.10. We depend on some libraries like CLIP and so on. Before starting, install the required libraries using pip install -r requirements.txt
First execute one of the following notebooks to download raw reviews, item information and images. Depending on the dataset you want to generate, you would have to execute one of the following notebooks:
1a_download_amazon_data.ipynb
to download reviews and images for the Amazon Datasets1b_download_bookcrossing_data.ipynb
to download the Bookcrossing dataset1c_download_ml_data.ipynb
to download any of the Movielens datasets
To keep the notebooks smaller, the code for processing datasets is contained in three modules in the same folder amazon_dataset.py
, bookcrossing_dataset.py
and movielens_dataset.py
. Each of them exposes functions to load the items, images and reviews as pandas dataframes.