conv_rnn

Convolutional RNN

Implementation based on [1].

Usage

Run ./getData.sh to fetch the data. The project structure should now look like this:

├── conv_rnn/
│   ├── data/
│   ├── saves/
│   └── *.*

You may then run python train.py and python test.py for training and testing, respectively. For more options, add the -h switch.

Empirical results

Best dev	Test
48.1	48.9

References

[1] Chenglong Wang, Feijun Jiang, and Hongxia Yang. 2017. A Hybrid Framework for Text Modeling with Convolutional RNN. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '17).