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https://github.com/r-papso/recobert
RecoBERT: A Catalog Language Model for Text-Based Recommendations
https://github.com/r-papso/recobert
deep-leaning natural-language-processing recommender-system
Last synced: 1 day ago
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RecoBERT: A Catalog Language Model for Text-Based Recommendations
- Host: GitHub
- URL: https://github.com/r-papso/recobert
- Owner: r-papso
- License: mit
- Created: 2022-12-08T11:41:20.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2022-12-30T16:14:08.000Z (almost 2 years ago)
- Last Synced: 2024-06-09T14:28:55.770Z (5 months ago)
- Topics: deep-leaning, natural-language-processing, recommender-system
- Language: Python
- Homepage:
- Size: 40 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# RecoBERT
This repository contains implementation of the paper RecoBERT: A Catalog Language Model for Text-Based Recommendations [1]. This is NOT the original implenetation of the paper.
The paper can be found here: https://arxiv.org/pdf/2009.13292.pdf
## Requirements
```bash
python==3.9.15
pandas==1.5.2
pytorch==1.13.0
transformers==4.25.1
```
## Datasets
Preprocessed wines dataset used for RecoBERT training and evaluation along with annotated test subset can be found on this [link](https://drive.google.com/file/d/1oxtPgy14t3rdd5g_AVpiRRfquZU-5MFJ/view?usp=sharing).
## Usage
To train and/or evaluate the RecoBERT implementation:
1. Download preprocessed wines dataset from this [link](https://drive.google.com/file/d/1oxtPgy14t3rdd5g_AVpiRRfquZU-5MFJ/view?usp=sharing).
2. Save the dataset to the ./data folder within this repository.
3. Run training by using command: ```python ./scripts/training.py wines```.
4. After training, run inference by using command: ```python ./scripts/inference.py wines```.
## References
[1] I. Malkiel, O. Barkan, A. Caciularu, N. Razin, O. Katz and N. Koenigstein, "RecoBERT: A Catalog Language Model for Text-Based Recommendations," 2020.