Cross_Domain_Hedge_Detection

We implement the cross domain Chinese hedge detection using Keras.

DataSet

This dataset contains four domains: wiki, biomedical abstract, discuss and result.

For example, we use the abstract to train and test for the wiki, this is called wiki_by_abstract (test_by_train).

We use five fold test to evaluate our model.

word embedding

We train our word embedding on a small corpus downloaded from the Medline, we will make our word embedding public as soon as possible.
We would like to make our data public as soon as possible.

Use

• python 2.7
• Keras 2.0.1
• Tensorflow 1.0.1
• nltk 3.2.2
• tqdm

Run

To creature the data and features

python hedge_process.py

To process the data into the matrix and use for learning

python process_data.py

To run the BiLSTM model

python main.py