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SMAE

This is the code for "Learning Sentiment Memories for Sentiment Modification without Parallel Data".

Install / Use

/learn @lancopku/SMAE
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

SMAE

This is the code for "Learning Sentiment Memories for Sentiment Modification without Parallel Data".

Environment and Dependency

  • Ubuntu 16.04
  • Python 3.5
  • Tensorflow 1.4
  • nltk 3.2.5

Data

yelp

Usage

CUDA_VISIBLE_DEVICES=0 python3 main.py
To run this code, you first need to process the dataset into the specific format. We provide the sample file in dataset to facilitate runing code. But these files are just a small piece of the complete training set and are not enough to get a satisfied performance. You can process the data provided by yelp to get enough training set. During running, several files will be created.

The full dataset we used in our experiments can be found here: full_data

Feel free to contact me if you have any questions:)

Cite

If you use this code for your research, please cite the following paper:

  @inproceedings{zhang2018learning,  
  author = {Zhang, Yi and Xu, Jingjing and Yang, Pengcheng and Sun, Xu},  
  title = {Learning Sentiment Memories for Sentiment Modification without Parallel Data},  
  booktitle = {EMNLP 2018},  
  year = {2018}  
  }  
View on GitHub
GitHub Stars55
CategoryEducation
Updated2mo ago
Forks11

Languages

Python

Security Score

80/100

Audited on Jan 12, 2026

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