https://github.com/smartdataanalytics/polisis_benchmark
Reproducing state-of-the-art results
https://github.com/smartdataanalytics/polisis_benchmark
Last synced: 5 months ago
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Reproducing state-of-the-art results
- Host: GitHub
- URL: https://github.com/smartdataanalytics/polisis_benchmark
- Owner: SmartDataAnalytics
- Created: 2020-02-13T10:09:24.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2023-02-02T05:13:35.000Z (about 2 years ago)
- Last Synced: 2024-04-16T07:41:35.702Z (about 1 year ago)
- Language: Python
- Size: 2.19 MB
- Stars: 17
- Watchers: 14
- Forks: 4
- Open Issues: 16
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Metadata Files:
- Readme: README.md
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README
# Polisis_Benchmark
Reproducing state-of-the-art results
This repo is our effort to reproduce Polisis results for privacy policy classification based on their paper: https://arxiv.org/abs/1802.02561
# Setup instructions
1. Setup a virtual environment using any tool (e.g., conda) and activate it: conda -n privacy_policy python=3.6 source activate privacy_policy
2. Install dependecies from the requirement file: pip install -r requirement.txt
3. install NLTK tokenizer: python -m nltk.downloader punkt
# Usage instructions
To run the experiment: python -u cnn_multi_label_classifier.py
Parameters can be found in args.py
Important Note: By default the code will use GloVe embeddings. Due to licesing the in-domain embeddings can be provided only upon request.