The implementation of Mitigating Matthew Effect: Multi-Hypergraph Boosted Multi-Interest Self-Supervised Learning for Conversational Recommendation (EMNLP 2024)

Our paper can be viewed at here

Python venv

We use uv to manage HiCore's python venv. You can click this url for more details about uv.

uv venv --python 3.12

Dataset

The dataset will be automatically download after you run the repo's code. However, the item/entity/word edger should be built by followed command:

cd HiCore/
uv run run_edger.py -d redial

Or download the whole dataset and item/entity/word edger from here

Place the dataset in path HiCore/data.

How to run

Run the crslab framework by followed command:

cd HiCore/
uv run run_crslab.py -c config/crs/hicore/redial.yaml -g 0 -s 3407