This repository contains code for the paper "Memory-Based Matching Models for Multi-turn Response Selection in Retrieval-Based Chatbots".
This is the code by ECNU submitted to nlpcc2018 Task5 sub1. The MBMN(MVM)+SMN+NLP model achieves 62.61% Precision score on the test set and ranks 1st among all the participants.
# download the repo
git clone https://github.com/gongwu/nlpcc2018-Task5-MultiTurnResponseSelection.git
# download the dataset
# run the model
python main/run_dialogue_SCNRMA.py
| Model | Precision (%) | |
|---|---|---|
| NLP features | 39.67 | |
| SMN [ACL2017] | 61.76 | |
| Single model | MBMN(MVM) | 60.03 |
| MBMN(SMVM) | 61.97 | |
| MBMN(MVM)+SMN | 62.11 | |
| Combined model | MBMN(SMVM)+SMN | 62.08 |
| MBMN(MVM)+SMN+NLP | 62.26 | |
| MBMN(SMVM)+SMN+NLP | 62.16 |