Inter-Correlation

This repo contains the implementation of "Intra-Correlation Encoding for Chinese Sentence Intention Matching" in Keras & Tensorflow.

All codes you can find here:

Baidu Netdisk: https://pan.baidu.com/s/18yzI3RP0669H5RHI45_6zA password: gvdp

Usage for python code

0. Requirement

python 3.6
numpy==1.16.4
pandas==0.22.0
tensorboard==1.12.0
tensorflow-gpu==1.12.0
keras==2.2.4
gensim==3.0.0

1. Data preparation

The dataset is BQ & LCQMC.
"The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification", https://www.aclweb.org/anthology/D18-1536/.

"LCQMC: A Large-scale Chinese Question Matching Corpus", https://www.aclweb.org/anthology/C18-1166/.

2. Start the training process

python train.py

3. Start the prediction process

python predict.py

4. Load the trained model

You can download the codes and our trained model from here:

Baidu Netdisk: https://pan.baidu.com/s/18yzI3RP0669H5RHI45_6zA password: gvdp,

then run predict.py to get the experiment results in "Intra-Correlation Encoding for Chinese Sentence Intention Matching"

Reference

If you find our source useful, please consider citing our work.

Xu Zhang, Yifeng Li, Wenpeng Lu, Ping Jian, Guoqiang Zhang. Intra-Correlation Encoding for Chinese Sentence Intention Matching[C]//Proceedings of the 28th International Conference on Computational Linguistics. 2020: 5193-5204.

zhangxu90s/ICE