https://github.com/jonzarecki/textual-mqs

Implementation for the IJCAI20 paper "Textual Membership Queries"
https://github.com/jonzarecki/textual-mqs

active-learning augmentation natural-language-processing

Last synced: 11 months ago
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Implementation for the IJCAI20 paper "Textual Membership Queries"

• Host: GitHub
• URL: https://github.com/jonzarecki/textual-mqs
• Owner: jonzarecki
• Created: 2018-05-05T10:14:57.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2020-08-07T13:51:51.000Z (almost 6 years ago)
• Last Synced: 2025-03-22T11:19:58.663Z (about 1 year ago)
• Topics: active-learning, augmentation, natural-language-processing
• Language: Python
• Homepage:
• Size: 3.48 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Textual Membership Queries - Official Implementation

[[Arxiv]](https://arxiv.org/pdf/1805.04609.pdf) [[IJCAI]](https://www.ijcai.org/Proceedings/2020/0369.pdf)

Code for running the experiments presented in the IJCAI 20 paper "Textual Membership Queries" (Jonathan Zarecki, Shaul Markovitch).

In order to use this repository it is necessary to download files from our [Google Drive repository](https://drive.google.com/open?id=1ybCkW_m_OpLgQZnFnI5YFMocjIgnB3tN) and move them to their respective place in the file hierarchy.

#### Example Application of Modification Operators  

An example from the paper  of the modification operators applied to the "hate-speech" domain.

 ![Example of modification operators](actual_mod_ops_publish.png)

## Citation

If you use this code for your research, please cite our paper 

Textual Membership Queries:

```

@inproceedings{Zarecki2020TextualMQ,

  title={Textual Membership Queries},

  author={Jonathan Zarecki and Shaul Markovitch},

  booktitle={IJCAI},

  year={2020}

}

```