37 lines
981 B
Markdown
37 lines
981 B
Markdown
# HiCore
|
|
|
|
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](https://aclanthology.org/2024.emnlp-main.86/)
|
|
|
|
## Python venv
|
|
|
|
We use `uv` to manage HiCore's python venv. You can click this [url](https://docs.astral.sh/uv/) for more details about `uv`.
|
|
|
|
```bash
|
|
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:
|
|
|
|
```bash
|
|
cd HiCore/
|
|
uv run run_edger.py -d redial
|
|
```
|
|
|
|
Or download the whole dataset and item/entity/word edger from [here](https://drive.tokisakix.cn/share/9hQIhokW)
|
|
|
|
Place the dataset in path `HiCore/data`.
|
|
|
|
## How to run
|
|
|
|
Run the crslab framework by followed command:
|
|
|
|
```bash
|
|
cd HiCore/
|
|
uv run run_crslab.py -c config/crs/hicore/redial.yaml -g 0 -s 3407
|
|
``` |