Doc2VecC

code from the paper Efficient Vector Representation for Documents Through Corruption.

Acknowledge

The code was modified from Thomas Mikolov's code on Paragraph Vector. https://groups.google.com/forum/#!msg/word2vec-toolkit/Q49FIrNOQRo/J6KG8mUj45sJ

Dependencies

You will need to download the liblinear package, and change the path to the package in the script accordingly. https://www.csie.ntu.edu.tw/~cjlin/liblinear/

Getting started

Run the script go.sh, it will download the IMDB movie review dataset, and learn document representations on this dataset. A linear SVM is trained on the learned representation fo sentiment analysis.

Reference

If you found this code useful, please cite the following paper:

Minmin Chen. "Efficient Vector Representation for Documents Through Corruption." 5th International Conference on Learning Representations, ICLR (2017).

@article{chen2017efficient,
  title={Efficient Vector Representation for Documents Through Corruption},
  author={Chen, Minmin},
  journal={5th International Conference on Learning Representations},
  year={2017}
}

License

Apache License 2.0