Skip to content

This is our implementation of NARRE:Neural Attentional Regression with Review-level Explanations

Notifications You must be signed in to change notification settings

jeongin601/NARRE

This branch is up to date with chenchongthu/NARRE:master.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

author
Chong Chen
Apr 30, 2018
af17e18 · Apr 30, 2018

History

10 Commits
Apr 14, 2018
Apr 14, 2018
Apr 14, 2018
Apr 14, 2018
Apr 14, 2018
Apr 30, 2018

Repository files navigation

NARRE

This is our implementation for the paper:

Chong Chen, Min Zhang, Yiqun Liu, and Shaoping Ma. 2018. Neural Attentional Rating Regression with Review-level Explanations. In WWW'18.

Please cite our WWW'18 paper if you use our codes. Thanks!

@inproceedings{chen2018neural,
  title={Neural Attentional Rating Regression with Review-level Explanations},
  author={Chen, Chong and Zhang, Min and Liu, Yiqun and Ma, Shaoping},
  booktitle={Proceedings of the 2018 World Wide Web Conference on World Wide Web},
  pages={1583--1592},
  year={2018},
}

Author: Chong Chen (cstchenc@163.com)

Environments

  • python 2.7
  • Tensorflow (version: 0.12.1)
  • numpy
  • pandas

Dataset

In our experiments, we use the datasets from Amazon 5-core(http://jmcauley.ucsd.edu/data/amazon) and Yelp Challenge 2017(https://www.yelp.com/dataset_challenge).

Example to run the codes

Data preprocessing:

python loaddata.py	
python data_pro.py

Train and evaluate the model:

python train.py

Last Update Date: April 14, 2018

About

This is our implementation of NARRE:Neural Attentional Regression with Review-level Explanations

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%